ORIGINAL_ARTICLE
Structural Relationship of Sustainable Manufacturing Divers and Incentives
This paper is to study the factors that encourage, drive or force companies to alter manufacturing processes in a way that simultaneously minimizes their environmental and social effects and is cost-efficient for the companies. The principal focus of this research is on the relationships of these drivers, and their mutual influence on each other. This research is descriptive, and a case study is conducted in automotive plastic parts industry in Iran. After recognizing the drivers of sustainable manufacturing, they were localized, and finally ten drivers were approved. Then the relationships between the drivers were analyzed applying Grey-DEMATEL method. The most effective and important drivers in the macro-environment are laws and media, and in the micro-environment, competitors and customers are the key drivers. Business benefits and partners transfer the influences of cause drivers to effect divers. Managers, owners and personnel are the most effected drivers.
https://aie.ut.ac.ir/article_62208_324e4bfc25b79a9a47529b0b0dabe937.pdf
2017-06-22
133
146
10.22059/jieng.2017.62208
Grey DEMATEL
Sustainability drivers and incentives
Sustainable manufacturing
Mohammad aslam
Hosseinbor
m.a.hosseinbor@gmail.com
1
Department of Industrial Management, University of Mazandaran, Iran
AUTHOR
Abdolhamid
Safaei Qadikolaei
ab.safaei@umz.ac.ir
2
Department of Industrial Management, University of Mazandaran, Iran
LEAD_AUTHOR
Mehrdad
Madhooshi
madhoshi@umz.ac.ir
3
Department of Industrial Management, University of Mazandaran, Iran
AUTHOR
Mittal, V. K. and Sangwan, K. S. (2011). “Development of an interpretive structural model of obstacles to environmentally conscious technology adoption in Indian industry”, Glocalized Solutions for Sustainability in Manufacturing, Springer, Berlin Heidelberg, PP. 448-453 .
1
Brundtland, G., Khalid, M., Agnelli, S., Al-Athel, S., Chidzero, B., Fadika, L., Hauff, V., Lang, I., Shijun, M. and de Botero, M. M. (1987). Our Common Future ('Brundtland report'). UN.
2
Leff, E. (1995). Green production: toward an environmental rationality, Guilford Press, New York.
3
Govindan, K., Diabat, A. and Shankar, K. M. (2015). “Analyzing the drivers of green manufacturing with fuzzy approach”, Journal of Cleaner Production, Vol. 1, No. 96, PP. 182–193.
4
Jawahir, I. and Dillon, O. (2007). “Sustainable manufacturing processes: new challenges for developing predictive models and optimization techniques”, Proceedings of the First International Conference on Sustainable Manufacturing, Montreal, Canada, PP. 1–19.
5
US Department of Commerce, (2010(. “How does commerce define sustainable manufacturing”, It’s online at: http://www.trade.gov/competitiveness/ sustainablemanufacturing/how doc defines SM.asp.
6
Malik, M., Abdallah, S. and Hussain, M. (2016). “Assessing supplier environmental performance: Applying analytical hierarchical process in the United Arab Emirates healthcare chain”, Renewable and Sustainable EnergyReviews, Vol. 6. No. 55, PP. 1313–1321.
7
Srivastava, S. K. (2007). “Green supply‐chain management: a state‐of‐the‐art literature review.” International Journal of Management Reviews, Vol. 9, No. 1, PP. 53–80.
8
Agan, Y., Acar, M. F. and Borodin, A. (2013). “Drivers of environmental processes and their impact on performance: a study of Turkish SMEs”, Journal of Cleaner Production, Vol. 15, No. 51, PP. 23–33.
9
10. Joshi, K., Venkatachalam, A. and Jawahir, I. (2006). “A new methodology for transforming 3R concept into 6R concept for improved product sustainability”, IV Global Conference on Sustainable Product Development and Life Cycle Engineering. PP. 3–6.
10
11. Abdul-Rashid, S. H. H., Sakundarini, N., Raja Ghazilla, R. A. and Thurasamy, R. (2017). “The impact of sustainable manufacturing practices on sustainability performance: empirical evidence from Malaysia”, International Journal of Operations & Production Management, Vol. 37, No. 2, PP. 182-204.
11
12. Shankar, K. M., Kumar, P. U. and Kannan, D. (2016). “Analyzing the Drivers of Advanced Sustainable Manufacturing System Using AHP Approach”, Sustainability, Vol. 8, No. 8, PP. 824-835.
12
13. Smith, P., Gaffney, M., Shi, W., Hoard, S., Armendariz, I. I. and Mueller, D. (2017). “Drivers and barriers to the adoption and diffusion of Sustainable Jet Fuel (SJF) in the US Pacific Northwest”, Journal of Air Transport Management, Vol. 6, No. 58, PP. 113–124.
13
14. Dubey, R., Gunasekaran, A., Papadopoulos, T., Childe, S. J., Shibin, K. and Wamba, S. F. (2017). “Sustainable supply chain management: framework and further research directions”, Journal of Cleaner Production, Vol. 141-150, No. 142, PP. 1119–1130.
14
15. Bhanot, N., Rao, P. V. and Deshmukh, S. (2017). “An integrated approach for analyzing the enablers and barriers of sustainable manufacturing”, Journal of Cleaner Production, Vol.141-150, No. 142, Part 4, PP. 4412–4439.
15
16. Rauter, R., Jonker, J., & Baumgartner, R. J. (2017). “Going one's own way: drivers in developing business models for sustainability”, Journal of Cleaner Production, Vol. 131-140, No. 140, Part 1, PP. 144–154.
16
17. Fargani, H., Cheung, W. M. and Hasan, R. (2016). “An Empirical Analysis of the Factors That Support the Drivers of Sustainable Manufacturing”, Procedia CIRP, Vol. 56, PP. 491–495.
17
18. Andelin, M., Sarasoja, A. L., Ventovuori, T. and Junnila, S. (2015). “Breaking the circle of blame for sustainable buildings–evidence from Nordic countries”, Journal of Corporate Real Estate, Vol. 17. No. 1, PP. 26–45.
18
19. Foerstl, K., Azadegan, A., Leppelt, T. and Hartmann, E. (2015). “Drivers of supplier sustainability: Moving beyond compliance to commitment”, Journal of Supply Chain Management, Vol. 51, No, 1, PP. 67–92.
19
20. Alblas, A. A., Peters, K., and Wortmann, J. C. (2014). “Fuzzy sustainability incentives in new product development: An empirical exploration of sustainability challenges in manufacturing companies”, International Journal of Operations and Production Management, Vol. 34, No. 4, PP. 513–545.
20
21. Stoughton, A. M. and Ludema, J. (2012). “The driving forces of sustainability”, Journal of Organizational Change Management, Vol. 25, No. 4, PP. 501–517.
21
22. Diabat, A. and Govindan, K. (2011). “An analysis of the drivers affecting the implementation of green supply chain management.” Resources, Conservation and Recycling, Vol. 55, No. 6, PP. 659–667.
22
23. Khidir ElTayeb, T., Zailani, S. and Jayaraman, K. (2010). “The examination on the drivers for green purchasing adoption among EMS 14001 certified companies in Malaysia”, Journal of Manufacturing Technology Management, Vol. 21, No. 2, PP. 206–225.
23
24. Luken, R. and Van Rompaey, F. (2008). “Drivers for and barriers to environmentally sound technology adoption by manufacturing plants in nine developing countries”, Journal of Cleaner Production, Vol. 16, No. 1, PP. S67–S77.
24
25. Studer, S., Welford, R. and Hills, P. (2006). “Engaging Hong Kong businesses in environmental change: drivers and barriers”, Business Strategy and the Environment, Vol. 15, No. 6, PP. 416–431.
25
26. Gutowski, T., Murphy, C., Allen, D., Bauer, D., Bras, B., Piwonka, T., Sheng, P., Sutherland, J., Thurston, D. and Wolff, E. (2005). “Environmentally benign manufacturing: observations from Japan, Europe and the United States”, Journal of Cleaner Production, Vol. 13, No. 1, PP. 1–17.
26
27. Perez‐Sanchez, D., Barton, J. R. and Bower, D. (2003). “Implementing environmental management in SMEs”, Corporate Social Responsibility and Environmental Management, Vol. 10, No. 2, PP. 67–77.
27
28. Murphy, J. and Cohen, M. (2001). “Consumption, environment and public policy”, Exploring Sustainable Consumption: Environmental Policy and the Social Sciences, Elsevier, Oxford, PP. 3–20.
28
29. Gunningham, N. and Sinclair, D. (1997). “ACEL final report: barriers and motivators to the adoption of cleaner production practices”, Acel Final Report: Barriers and Motivators to the Adoption of Cleaner Production Practices, Australian Centre for Environmental Law.
29
30. Cuttance, P. and Ecob, R. (2009). Structural modeling by example: Applications in educational, sociological, and behavioral research, Cambridge University Press.
30
31. Rajesh, R. (2017). “Technological capabilities and supply chain resilience of firms: A relational analysis using Total Interpretive Structural Modeling (TISM)”, Technological Forecasting and Social Change, Vol. 111-120, No. 181, PP. 161-169.
31
32. Tseng, M. L. (2009). “A causal and effect decision making model of service quality expectation using grey-fuzzy DEMATEL approach”, Expert Systems with Applications, Vol. 36, No. 4, PP. 7738–7748.
32
33. Julong, D. (1989). “Introduction to grey system theory”, The Journal of Grey System, Vol. 1, No. 1, PP. 1–24.
33
34. Bai, C. and Sarkis, J. (2013). “A grey-based DEMATEL model for evaluating business process management critical success factors”, International Journal of Production Economics, Vol. 146, No.1, PP. 281–292.
34
35. Yan, G., Liu, C. and Shao, Z. (2009). “Analysis of influencing factors for the grey multi-attribute group decision making, Grey Systems and Intelligent Services,” IEEE International Conference on, IEEE: 2009; PP. 1081–1086.
35
36. Opricovic, S. and Tzeng, G. H. (2003). “Defuzzification within a multicriteria decision model”, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 11, No. 5, PP. 635–652.
36
37. Sarkis, J., Gonzalez-Torre, P. and Adenso-Diaz, B. (2010). “Stakeholder pressure and the adoption of environmental practices: The mediating effect of training”, Journal of Operations Management, Vol. 28, No. 2, PP. 163–176.
37
38. Engert S, Rauter R, and Baumgartner, R. J. (2015). “Exploring the integration of corporate sustainability into strategic management: a literature review,” Journal of Cleaner Production. Vol. 1. No. 112, PP. 2833–2850.
38
39. Lozano, R. (2015). “A holistic perspective on corporate sustainability drivers”, Corporate Social Responsibility and Environmental Management, Vol. 22, No. 1, PP. 32–44.
39
ORIGINAL_ARTICLE
A Genetic Algorithm for Integration of Vehicle Routing Problem and Production Scheduling in Supply Chain (Case Study: Medical Equipment Supply Chain)
This paper studies a model for integration of vehicle routing problem (VRP) in a supply chain with order assignment to the suppliers and determining their production sequence. The considered supply chain consists of some suppliers, vehicles and a manufacturer. It is assumed that manufacturer purchases identify the raw material demand of suppliers in wholesale all at once. This provides the opportunity of receiving discounts and consequently decreasing final price. A transportation fleet composed of some vehicles, each of which may have a different speed and different transport capacity, is responsible for transporting purchased raw materials to suppliers and gathering completed parts from them aiming at minimizing the total tardiness of all jobs. After presenting the mathematical model of the problem, a dynamic genetic algorithm with two dimensional structures is proposed. The algorithm was applied to the supply chain of a medical equipment manufacturer and the results were compared with real results beforehand. Findings show that applying dynamic genetic algorithm results in improving the average of tardiness from 9.44 days to 2.11 days. Also the comparison of dynamic genetic algorithm with the optimum solution for the small size problems, and the algorithm proposed for the nearest problem in the literature to our problem shows the high efficiency of dynamic genetic algorithm.
https://aie.ut.ac.ir/article_62209_eb0ebd187484e516059ac15f305e75b0.pdf
2017-06-22
147
160
10.22059/jieng.2017.62209
Genetic Algorithm
Medical equipment
Router
Scheduling
Supply Chain
Mohammad Ali
Beheshtiniya
beheshtinia@semnan.ac.ir
1
Faculty of Engineering, Semnan University, Iran
LEAD_AUTHOR
Atena
Aarabi
aarabi.atena@gmail.com
2
Faculty of Engineering, Semnan University, Iran
AUTHOR
1. Nasiri, M. and PourmohamadZia, N. (2015). “A Hybrid model for supplier selection and order allocation in supply chain”, Journal of Industrial Engineering, Vol. 49, No. 1, PP. 117–128.
1
2. Omrani, H. and Adabi, F. (2016). “A multi objective planning for supply chain network design with efficient manufacturers and distributers”, Journal of Industrial Engineering, Vol. 50, No. 2, PP. 261–278.
2
3. Lee, Y. H., Jeong, C. S. and Moon, C. (2002). “Advanced planning and scheduling with outsourcing in manufacturing supply chain”, Computers and Industrial Engineering, Vol. 43, No. 1–2, PP. 351–374.
3
4. Berning, G., et al. (2004). “Integrating collaborative planning and supply chain optimization for the chemical process industry (I)—methodology”, Computers & Chemical Engineering, Vol. 28, No. 6–7, PP. 913–927.
4
5. Naso, D. et al. (2007). “Genetic algorithms for supply-chain scheduling: A case study in the distribution of ready-mixed concrete”, European Journal of Operational Research, Vol. 177, No. 3, PP. 2069–2099.
5
6. Averbakh, I. and Xue, Z. (2007). “On-line supply chain scheduling problems with preemption." European Journal of Operational Research, Vol. 181, No. 1, PP. 500–504.
6
7. Zegordi, S. and Beheshti Nia, M. (2009). “Integrating production and transportation scheduling in a two-stage supply chain considering order assignment”, The International Journal of Advanced Manufacturing Technology, Vol. 44, No. 9–10, PP. 928–939.
7
8. Sawik, T. (2009). “Coordinated supply chain scheduling." International Journal of Production Economics, Vol. 120, No. 2, PP. 437–451.
8
9. Su, C.-S., Pan, J.C.-H. and Hsu, T.-S. (2009). "A new heuristic algorithm for the machine scheduling problem with job delivery coordination”, Theoretical Computer Science, Vol. 410, No. 27–29, PP. 2581–2591.
9
10. Averbakh, I. (2010). “On-line integrated production–distribution scheduling problems with capacitated deliveries”, European Journal of Operational Research, Vol. 200, No. 2, PP. 377–384.
10
11. Scholz-Reiter, B., Frazzon, E.M. and Makuschewitz, T. (2010). “Integrating manufacturing and logistic systems along global supply chains”, CIRP Journal of Manufacturing Science and Technology, Vol. 2, No. 3, PP. 216–223.
11
12. Yimer, A.D. and Demirli, K. (2010). “A genetic approach to two-phase optimization of dynamic supply chain scheduling”, Computers and Industrial Engineering, Vol. 58, No. 3, PP. 411–422.
12
13. Fahimnia, B., Luong, L.and Marian, R. (2012). “Genetic algorithm optimisation of an integrated aggregate production–distribution plan in supply chains”, International Journal of Production Research, Vol. 50, No. 1, PP. 81–96.
13
14. Ullrich, C.A. (2013). “Integrated machine scheduling and vehicle routing with time windows”, European Journal of Operational Research, Vol. 227, No. 1, PP. 152–165.
14
15. Selvarajah, E. and Zhang, R. (2014). “Supply chain scheduling at the manufacturer to minimize inventory holding and delivery costs”, International Journal of Production Economics, Vol. 147, Part A, No. 0, PP. 117–124.
15
16. Low, C., et al. (2014). “Coordination of production scheduling and delivery problems with heterogeneous fleet”, International Journal of Production Economics, Vol. 153, No. 1, PP. 139–148.
16
17. Cheng, B., Yang, Y. and Hu, X. (2015). “Supply chain scheduling with batching, production and distribution”, International Journal of Computer Integrated Manufacturing, Vol., No. ahead-of-print, PP. 1–12.
17
18. Chang, Y.-C., Chang, K.-H. and Kang, T.-C. (2015). “Applied Variable Neighborhood Search-Based Approach to Solve Two-Stage Supply Chain Scheduling Problems”, Journal of Testing and Evaluation, Vol. 44, No. 3, PP. 1337-1349.
18
19. Tasan, A. S. and Gen, M. (2012). “A genetic algorithm based approach to vehicle routing problem with simultaneous pick-up and deliveries”, Computers and Industrial Engineering, Vol. 62, No. 3, PP. 755–761.
19
ORIGINAL_ARTICLE
An Efficient Imperialist Competitive Algorithm for Resource Constrained Project Scheduling Problem
In this paper, a new algorithm based on the framework of the imperialist competitive algorithm for solving resource constrained project scheduling problem (RCPSP) will be proposed. In this problem, the activities are scheduled based on the resource and precedence relationships constraints in a way that the makes pan will be minimized. In order to model the assimilation process, a uniform crossover has been used, and to avoid premature convergence of the proposed algorithm, two revolution operators including one point revolution and multi-point revolution will be introduced. Also, in order to enhance the exploitation ability, a combined local search including permutation based local search (PBLS) and forward-backward improvement (FBI) is performed. The algorithm parameters are determined by designing Taguchi experiment, and the efficiency of proposed ICA is demonstrated by solving PSPLIB problems. Computational results and comparisons with some existing algorithms show that the proposed algorithm can produce near-optimal solution for small problems and competitive solution for large ones.
https://aie.ut.ac.ir/article_62210_c4f5cca97cf4ea25be4b2a6cb19cb261.pdf
2017-06-22
161
174
10.22059/jieng.2017.62210
Imperialist competitive algorithm
Optimization Algorithm
Resource constrained project scheduling problem
Iman
Panahi
iman.panahi.c@gmail.com
1
Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
AUTHOR
Nasim
Nahavandi
n_nahavandi@modares.ac.ir
2
Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
LEAD_AUTHOR
1. Blazewicz, J., Lenstra, J. and Rinnoy Kan, A. H. (1983). “Scheduling subject to resource classification and complexity constraint.”, Discret. Appl. Math., Vol. 5, No. 1, PP. 11–24.
1
2. Hartmann, S. (1997). Scheduling medical research experiments: an application of project scheduling methods, Technical Report, University Kiel, Germany.
2
3. Alba, E. and Francisco Chicano, J. (2007). “Software project management with Gas”, Information Sciences, Vol. 177, No. 11, PP. 2380–2401.
3
4. Dodin, B., Elimam, A. A. and Rolland, E. (1998). “Tabu search in audit scheduling.”, European Journal of Operational Research, Vol. 106, No. 2–3, PP. 373–392.
4
5. Sprecher, A. (1994). “Special cases”, In Resource-constrained project scheduling: Exact methods for the multi-mode case,1th Ed,PP. 10–18, Springer, Berlin, Germany.
5
6. Demeulemeester, E. L. and Herroelen, W. S. (2002). The Resource-Constrained Project Scheduling Problem, In Project Scheduling: A Research Handbook, 1th Ed, PP. 203–342, Springer, Berlin, Germany.
6
7. Hartmann, S. (1998). “A competitive genetic algorithm for resource-constrained project scheduling”, Naval Research Logistics, Vol. 45, No. 6, PP. 733–750.
7
8. Hartmann, S. (2002). “A self-adapting genetic algorithm for project scheduling under resource constraints”, Naval Research Logistics, Vol. 49, No. 5, PP. 433–448
8
9. Bouleimen, K. and Lecocq, H. (2003). “A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version”, European Journal of Operational Research, Vol. 149, No. 2, PP. 268–281.
9
10. Valls, V., Ballestín, F. and Quintanilla, S. (2008). “A hybrid genetic algorithm for the resource-constrained project scheduling problem”, European Journal of Operational Research, Vol. 185, No. 2, PP. 495–508.
10
11. Ziarati, K., Akbari, R. and Zeighami, V. (2011). “On the performance of bee algorithms for resource-constrained project scheduling problem”, Applied Soft Computing, Vol. 11, No. 4, PP. 3720–3733.
11
12. Fang, C. and Wang, L. (2012). “An effective shuffled frog-leaping algorithm for resource-constrained project scheduling problem”, Computers & Operations Research, Vol. 39, No. 5, PP. 890–901.
12
13. Fahmy, A., Hassan, T. M. and Bassioni, H. (2014). “Improving RCPSP solutions quality with Stacking Justification—Application with particle swarm optimization”, Expert Systems with Applications, Vol. 41, No. 13, PP. 5870–5881.
13
14. Zheng, X. and Wang, L. (2015). “A multi-agent optimization algorithm for resource constrained project scheduling problem”, Expert Systems with Applications, Vol. 42, No. 15–16, PP. 6039–6049.
14
15. Atashpaz-Gargari, E. and Lucas, C. (2007). “Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition”, IEEE Congress on Evolutionary Computation, PP. 4661–4667.
15
16. Hosseini, S. and Al Khaled, A. (2014). “A survey on the Imperialist Competitive Algorithm metaheuristic: Implementation in engineering domain and directions for future research”, Applied Soft Computing, Vol. 24, PP. 1078–1094.
16
17. Kolisch, R. (1996). “Serial and parallel resource-constrained project scheduling methods revisited: Theory and computation”, European Journal of Operational Research, Vol. 90, No. 95, PP. 320–333.
17
18. Li, K. Y. and Willis, R. J. (1992). “An iterative scheduling technique for resource-constrained project scheduling”, European Journal of Operational Research, Vol. 56, No. 3, PP. 370–379.
18
19. Kolisch, R. and Sprecher, A. (1997). “PSPLIB - A project scheduling problem library”, European Journal of Operational Research, Vol. 96, No. 1, PP. 205–216.
19
20. Kolisch, R. and Drexl, A. (1996). “Adaptive search for solving hard project scheduling problems”, Naval Research Logistics, Vol. 43, No. 1, PP. 23–40.
20
21. Schirmer, A. (2000). “Case-based reasoning and improved adaptive search for project scheduling. Naval Research Logistics”, Naval Research Logistics, Vol. 47, No. 3, PP. 201–222.
21
22. Coelho, J. and Tavares, L. (2005). “Comparative analysis of metaheuristics for the resource constrained project scheduling problem”, European Journal of Operational Research, Vol. 165, PP. 375–386.
22
23. Agarwal, A., Colak, S. and Erenguc, S. (2011). “A Neurogenetic approach for the resource-constrained project scheduling problem”, Computers & Operations Research, Vol. 38, No. 1, PP. 44–50.
23
24. Kolisch, R. and Hartmann, S. (2006). “Experimental investigation of heuristics for resource-constrained project scheduling: An update”, European Journal of Operational Research, Vol. 174, No. 1, PP. 23–37.
24
ORIGINAL_ARTICLE
A Hybrid Algorithm to Solve a Bi-objective Location Routing Inventory Problem in a Supply Chain under Stochastic Demand
Nowadays, fierce competition in global markets has forced companies to improve the design and management of supply chains, and provide competitive advantages. Decision integrity is one of the main factors which highly lead to a considerable reduction of supply chain costs, and higher costumer’s satisfaction. Distribution network design is based on three major problems: location allocation, vehicle routing and inventory control. Since the effective role of reducing distribution costs in the survival of the supply chain is clear to all, in this paper, these three problems will be incorporated into an integrated model under demand uncertainty. This approach leads to the significant reduction of distribution costs, higher customer satisfaction, and also providing an efficient supply chain. Also in this study, in addition to minimizing the total cost including fixed cost of establishing depots, transportation costs and inventory costs, the customers’ satisfaction will increase by reducing their waiting time. So, a bi-objective mixed integer non-linear model is presented by using chance constrained programming, where customer demands are assumed to have a normal distribution. Then, to solve the model, a hybrid algorithm based on simulated annealing and genetic algorithm is proposed, and is evaluated on a set of instances. The computational results illustrate the algorithm efficiency to solve a wide range of problems with different sizes.
https://aie.ut.ac.ir/article_62211_4561cb6c7e7c43d14ccb23b068367616.pdf
2017-06-22
175
193
10.22059/jieng.2017.62211
Facility location
Integrated supply chain
Inventory Control
Metaheuristic algorithms
Vehicle routing
Ebrahim
Teymouri
teimoury@iust.ac.ir
1
Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
LEAD_AUTHOR
Fatemeh
Aboutorabiyan
aboutorabian@ut.ac.ir
2
Faculty of Engineering, University of Tehran, Iran
AUTHOR
Mohammad Hosein
Babaei
3
Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
AUTHOR
Salhi, S. and Rand, G. K. (1989). “The effect of ignoring routes when locating depots”, European Journal of Operational Research, Vol. 39, No. 2, PP. 150–156.
1
Ahmadi Javid, A. and Seddighi, A. H. (2012). “A location-routing-inventory model for designing multisource distribution networks”, Engineering Optimization, Vol. 44, No. 6, PP. 637–656.
2
Teimoury, E., Modarres, M., Ghasemzadeh, F. and Fathi, M. (2010). “A queueing approach to production-inventory planning for supply chain with uncertain demands: Case study of PAKSHOO Chemicals Company”, Journal of Manufacturing Systems, Vol. 29, No. 2, PP 55–62.
3
Min, H., Jayaraman, V. and Srivastava, R. (1998). “Combined location-routing problems: A synthesis and future research directions”, European Journal of Operational Research, Vol. 108, No. 1, PP. 1–15.
4
Nagy, G. and Salhi, S. (2007). “Location-routing: Issues, models and methods”, European Journal of Operational Research, Vol. 177, No. 2, PP. 649–672.
5
Quintero‐Araujo, C. L., Caballero‐Villalobos, J. P., Juan, A. A. and Montoya‐Torres, J. R. (2016). “A biased‐randomized metaheuristic for the capacitated location routing problem”, International Transactions in Operational Research, Vol. 24, No. 5, PP. 1079-1098.
6
Baita, F., Ukovich, W., Pesenti, R. and Favaretto, D. (1998). “Dynamic routing-and-inventory problems: a review”, Transportation Research Part A: Policy and Practice, Vol. 32, No. 8, PP. 585–598.
7
Jaillet, P., Bard, J. F., Huang, L. and Dror, M. (2002). “Delivery cost approximations for inventory routing problems in a rolling horizon framework”, Transportation Science, Vol. 36, No. 3, PP. 292–300.
8
Kleywegt, A. J., Nori, V. S. and Savelsbergh, M. W. (2002). “The stochastic inventory routing problem with direct deliveries”, Transportation Science, Vol. 36, No. 1, PP. 94–118.
9
Adelman, D. (2004). “A price-directed approach to stochastic inventory/routing”, Operations Research, Vol. 52, No. 4, PP. 499–514.
10
Gaur, V. and Fisher, M. L. (2004). “A periodic inventory routing problem at a supermarket chain.” Operations Research, Vol. 52, No. 6, PP. 813–822.
11
Zhao, Q. H., Chen, S. and Zang, C. X. (2008). “Model and algorithm for inventory/routing decision in a three-echelon logistics system”, European Journal of Operational Research, Vol. 191, No. 3, PP. 623–635.
12
Yu, Y., Chen, H. and Chu, F. (2008). “A new model and hybrid approach for large scale inventory routing problems”, European Journal of Operational Research, Vol. 189, No. 3, PP. 1022–1040.
13
Day, J. M., Wright, P. D., Schoenherr, T., Venkataramanan, M. and Gaudette, K. (2009). “Improving routing and scheduling decisions at a distributor of industrial gasses”, Omega, Vol. 37, No. 1, PP. 227–237.
14
Andersson, H., Christiansen, M. and Desaulniers, G. (2016). “A new decomposition algorithm for a liquefied natural gas inventory routing problem”, International Journal of Production Research, Vol. 54, No. 2, PP. 564–578.
15
Daskin, M. S., Coullard, C. R. and Shen, Z. J. M. (2002). “An inventory-location model: Formulation, solution algorithm and computational results”, Annals of Operations Research, Vol. 110, No. 1, PP. 83–106.
16
Shen, Z. J. M., Coullard, C. and Daskin, M. S. (2003). “A joint location-inventory model”, Transportation Science, Vol. 37, No. 1, PP. 40–55.
17
Diabat, A., Richard, J. P. and Codrington, C. W. (2013). “A Lagrangian relaxation approach to simultaneous strategic and tactical planning in supply chain design”, Annals of Operations Research, Vol. 203, No. 1, PP. 55-80
18
Puga, M. S. and Tancrez, J. S. (2017). “A heuristic algorithm for solving large location–inventory problems with demand uncertainty”, European Journal of Operational Research, Vol. 259, No. 2, PP. 413–423.
19
Liu, S. C. and Lee, S. B. (2003). “A two-phase heuristic method for the multi-depot location routing problem taking inventory control decisions into consideration”, The International Journal of Advanced Manufacturing Technology, Vol. 22, No. 11, PP. 941–950.
20
Liu, S. C. and Lin, C. C. (2005). “A heuristic method for the combined location routing and inventory problem”, The International Journal of Advanced Manufacturing Technology, Vol. 26, No. 4, PP. 372–381.
21
Shen, Z. J. M. and Qi, L. (2007). “Incorporating inventory and routing costs in strategic location models”, European Journal of Operational Research, Vol. 179, No. 2, PP. 372–389.
22
Javid, A. A. and Azad, N. (2010). “Incorporating location, routing and inventory decisions in supply chain network design”, Transportation Research Part E: Logistics and Transportation Review, Vol. 46, No. 5, PP. 582–597.
23
Wang, C., Ma, Z. and Li, H. (2008, October). “Stochastic dynamic location-routing-inventory problem in closed-loop logistics system for reusing end-of-use products.” In Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference (Vol. 2, PP. 691–695). IEEE.
24
Sajjadi, S. R. and Cheraghi, S. H. (2011). “Multi-products location–routing problem integrated with inventory under stochastic demand”, International Journal of Industrial and Systems Engineering, Vol. 7, No. 4, PP. 454–476.
25
Guerrero, W. J., Prodhon, C., Velasco, N. and Amaya, C. A. (2013). “Hybrid heuristic for the inventory location-routing problem with deterministic demand”, International Journal of Production Economics, Vol. 146, No. 1, PP. 359–370.
26
Tavakkoli-Moghaddam, R., Forouzanfar, F. and Ebrahimnejad, S. (2013). “Incorporating location, routing, and inventory decisions in a bi-objective supply chain design problem with risk-pooling”, Journal of Industrial Engineering International, Vol. 9, No. 1, PP. 9-19
27
Tavakkoli-Moghaddam, R. and Raziei, Z. (2016). “A New Bi-Objective Location-Routing-Inventory Problem with Fuzzy Demands”, IFAC-PapersOnLine, Vol. 49, No. 12, PP. 1116–1121.
28
Turan, B., Minner, S. and Hartl, R. F. (2017). “A VNS approach to multi-location inventory redistribution with vehicle routing”, Computers and Operations Research, Vol. 78, February 2017,PP. 526–536.
29
Hiassat, A., Diabat, A. and Rahwan, I. (2017). “A genetic algorithm approach for location-inventory-routing problem with perishable products”, Journal of Manufacturing Systems, Vol. 42, January 2017,PP. 93–103.
30
Norouzi, N., Tavakkoli, M. R., Sadegh, A. M. and Khaefi, S. (2015). “New mathematical modeling for a facilities location and vehicle routing problem solving by a hybrid imperialist competitive algorithm.” Vol. 49, No. 1, PP. 129–137.
31
Gholami, M. and Honarvar, M. (2015). “Developing a Mathematical Model for Vendor Managed Inventory Considering Deterioration and Amelioration Items in a Three-Level Supply Chain”, Journal of Industrial Engineering???, Vol. 49, No. 2, PP. 237–256.
32
Kiani, M., Seidgar, H., Mahdavi, I. and Tavakkoli, M. R. (2015), “An Efficient Genetic Algorithm for a Vehicle Routing Problem Considering the Competency of Working Teams”, Journal of Industrial Engineering, Vol. 49, No. 2, PP. 257–271.
33
Cordeau, J. F., Laporte, G., Savelsbergh, M. W. P. and Vigo, D. (2006). “Vehicle Routing”, in Handbook of Operations Research and Management Science, Transportation, C. Barnhart and G. Laporte, Editors, Elsevier: Amsterdam, PP. 367–428.
34
Megiddo, N. and Supowit, K. J. (1984). “On the complexity of some common geometric location problems”, SIAM Journal on Computing, Vol. 13, No. 1, PP. 182–196.
35
Derbel, H., Jarboui, B., Hanafi, S. and Chabchoub, H. (2012). “Genetic algorithm with iterated local search for solving a location-routing problem”, Expert Systems with Applications, Vol. 39, No. 3, PP. 2865–2871.
36
Vincent, F. Y., Lin, S. W., Lee, W. and Ting, C. J. (2010). “A simulated annealing heuristic for the capacitated location routing problem”, Computers and Industrial Engineering, Vol. 58, No. 2, PP. 288–299.
37
Ting, C. J. and Chen, C. H. (2013). “A multiple ant colony optimization algorithm for the capacitated location routing problem”, International Journal of Production Economics, Vol. 141, No. 1, PP. 34–44.
38
Barreto, S., Ferreira, C., Paixao, J. and Santos, B. S. (2007). “Using clustering analysis in a capacitated location-routing problem”, European Journal of Operational Research, Vol. 179, No. 3, PP. 968–977.
39
Prins, C., Prodhon, C. and Calvo, R. W. (2006, April). “A memetic algorithm with population management (MA| PM) for the capacitated location-routing problem.” In European Conference on Evolutionary Computation in Combinatorial Optimization (PP. 183–194). Springer Berlin Heidelberg.
40
Contardo, C., Cordeau, J. F. and Gendron, B. (2014). “A GRASP+ ILP-based metaheuristic for the capacitated location-routing problem”, Journal of Heuristics, Vol. 20, No. 1, PP. 1–38.
41
ORIGINAL_ARTICLE
A Simultaneous Location, Routing and Scheduling Model for Transporting Evacuees with Time Window and Multiple Depots
After natural disasters and unexpected events, one of the most vital actions of disaster response phase is to transport evacuees from disaster areas to safe places. In this paper, decisions of the location of shelters and routing and scheduling of relief vehicles at the same time are modeled for a two-level network including depots of vehicles, affected areas, and shelters. In the evacuation operation, the possibility of servicing to evacuees in each affected area by several vehicles, existence of multiple depots of heterogeneous vehicles and time window constraints are considered. To solve the proposed model and demonstrate its efficiency, a numerical example was solved by exact method, and it was done the sensitivity analysis on the problem main parameters. Results show that the number of shelters to locate evacuees and capacity of relief vehicles effects on total times for vehicles to get to affected areas and shelters.
https://aie.ut.ac.ir/article_62212_e6a3ca6605f81882bc347b721371de47.pdf
2017-06-22
195
206
10.22059/jieng.2017.62212
Disaster management
Location of shelters
Routing
Scheduling
Fateme
Sabouhi
sabouhi@ind.iust.ac.ir
1
Faculty of Engineering, Iran University of Science and Technology, Tehran, Iran
AUTHOR
Ali
Bozorgi-Amiri
alibozorgi@ut.ac.ir
2
Faculty of Engineering, University of Tehran, Iran
LEAD_AUTHOR
Mahdi
Heydari
mheydari@iust.ac.ir
3
Faculty of Engineering, Iran University of Science and Technology, Tehran, Iran
AUTHOR
1- Ngueveu, S.U., Prins, C. and Calvo, R. W. (2010). “An effective memetic algorithm for the cumulative capacitated vehicle routing problem”, Computers & Operations Research., Vol. 37, No. 11, PP. 1877–1885.
1
2- Ribeiro, G. M. and Laporte, G. (2012). “An adaptive large neighborhood search heuristic for the cumulative capacitated vehicle routing problem.” Computers and Operations Research., Vol. 39, No. 3, PP. 728–735.
2
3- Ke, L. and Feng, Z. (2013). “A two-phase metaheuristic for the cumulative capacitated vehicle routing problem”, Computers and Operations Research., Vol. 40, No. 2, PP. 633–638.
3
4- Ozsoydan, F. B. and Sipahioglu, A. (2013). “Heuristic solution approaches for the cumulative capacitated vehicle routing problem”, Optimization., Vol. 62, No. 10, PP. 1321–1340.
4
5- Özdamar, L., Aksu, D.T. and Ergüneş, B. (2014). “Coordinating debris cleanup operations in post disaster road networks”, Socio-Economic Planning Sciences., Vol. 48, No. 4, PP. 249–262.
5
6- Wohlgemuth, S., Oloruntoba, R. and Clausen, U. (2012). “Dynamic vehicle routing with anticipation in disaster relief”, Socio-Economic Planning Sciences., Vol. 46, No. 4, PP. 261–271.
6
7- Lee, K., Lei, L., Pinedo, M. and Wang, S. (2013a). “Operations scheduling with multiple resources and transportation considerations”, International Journal of Production Research., Vol. 51, No. 23-24, PP. 7071-7090.
7
8- Lee, K., Lei, L. and Dong, H. (2013b). “A Solvable Case of Emergency Supply Chain Scheduling Problem with Multi-stage Lead Times”, Journal of Supply Chain and Operations Management., Vol. 11, No. 2, PP. 30–45.
8
9- Gan, X., Wang, Y., Kuang, J., Yu, Y. and Niu, B. (2014). “Emergency Vehicle Scheduling Problem with Time Utility in Disasters”, Mathematical Problems in Engineering, Vol. 2015, PP. 1-7.
9
10- Pramudita, A., Taniguchi, E. and Qureshi, A.G. (2014). “Location and Routing Problems of Debris Collection Operation after Disasters with Realistic Case Study”, Procedia-Social and Behavioral Sciences., Vol. 125, PP. 445–458.
10
11- Wex, F., Schryen, G., Feuerriegel, S. and Neumann, D. (2014). “Emergency response in natural disaster management: Allocation and scheduling of rescue units.” European Journal of Operational Research., Vol. 235, No. 3, PP. 697–708.
11
12- Bish, D. R. (2011). “Planning for a bus-based evacuation”, OR Spectrum., Vol. 33, No. 3, PP. 629–654.
12
13- Abdelgawad, H. and Abdulhai, B. (2011). “Large-scale evacuation using subway and bus transit: approach and application in city of Toronto”, Journal of Transportation Engineering, Vol. 138, No. 10, PP. 1215–1232.
13
14- Hamedi, M., Haghani, A. and Yang, S. (2012). “Reliable transportation of humanitarian supplies in disaster response: model and heuristic”, Procedia-Social and Behavioral Sciences., Vol. 54, PP. 1205–1219.
14
15- Rath, S. and Gutjahr, W. J. (2014). “A math-heuristic for the warehouse location–routing problem in disaster relief”, Computers and Operations Research., Vol. 42, PP. 25–39.
15
16- Gan, X., Wang, Y., Yu, Y. and Niu, B. (2013). “An emergency vehicle scheduling problem with time utility based on particle swarm optimization”, In Proceedings of the 9th international conference on Intelligent Computing Theories and Technology, PP. 614–623.
16
17- Wex, F., Schryen, G. and Neumann, D. (2012). “Operational emergency response under informational uncertainty: a fuzzy optimization model for scheduling and allocating rescue units”, In Proceedings of the 9th International ISCRAM Conference, PP. 1-10.
17
18- Talarico, L., Meisel, F. and Sorensen, K. (2015) “Ambulance routing for disaster response with patient groups”, Computers and Operations Research, Vol. 56, PP. 120–133.
18
19- Caunhye, A. M., Zhang, Y., Li, M. and Nie, X. (2016). “A location-routing model for prepositioning and distributing emergency supplies”, Transportation Research Part E: Logistics and Transportation Review, Vol. 90, PP. 161–176.
19
ORIGINAL_ARTICLE
A Hierarchical Approach for Lot-sizing and Production Scheduling of Complementary Product Packages
The lot sizing and scheduling problems for quick response to the diverse customers’ demands through the optimal utilization of resources and reducing the costs has a particular importance. In this paper, it is investigated the lot sizing and scheduling problem for complementary products. Each package consists of several complementary products with certain portions and different processing times, producing on the parallel production lines in a make-to-stock environment. To solve the problem, it is proposed a hierarchical approach with the objectives of minimizing the package costs, bound and stock, and maximizing the capacity utilization at the first level, and the aim of minimizing the completion time of complementary products at the second level. The second level model is difficult-to-solve in the large-sized instances; therefore, a rolling horizon heuristic solution algorithm is developed whose comparing performance to the exact solution as well as a proposed lower bound in different numerical examples, show the solution quality and its appropriate computation time. To validate the model, the actual data of a tile factory have been employed. Results show that the production plan, costs and times to complete the packages are improved, compared to the current process in the factory.
https://aie.ut.ac.ir/article_62213_8c125ff52fc29f3ae6cf04621ec0c150.pdf
2017-06-22
207
222
10.22059/jieng.2017.62213
Complementary product package
Heuristic algorithm
Hierarchical planning
Lot-sizing
Production Scheduling
Najmeh
Abbasi Hafshejani
najmeh.abbasi246@gmail.com
1
Department of Industrial Engineering, Yazd University, Iran
AUTHOR
Mohammad Mahdi
Lotfi
lotfi@yazd.ac.ir
2
Department of Industrial Engineering, Yazd University, Iran
LEAD_AUTHOR
Mahboobe
Honarvar
mhonarvar@yazd.ac.ir
3
Department of Industrial Engineering, Yazd University, Iran
AUTHOR
1. Ramezanian, R., Mehrabad, M. S. and Teimoury, E. (2013). “A mathematical model for integrating lot-sizing and scheduling problem in capacitated flow shop environments”, Intrnational Journal Of Advanced Manufacturing Technology, Vol. 66, No. 1, PP. 347–361.
1
2. Baker, K. R. (1974). Introduction to sequencing and scheduling, John Wiley and Sons, New York.
2
3. Hax, A. C. and Meal, H. C. (1973). Hierarchical integration of production planning and scheduling, Massachusetts Institute of Technology, Operations Research Center.
3
4. Gupta, D. and Magnusson, T. (2005). “The capacitated lot-sizing and scheduling problem with sequence-dependent setup costs and setup times”, Computers & Operations Research., Vol. 32, No. 4, PP. 727–747.
4
5. Sawik, T. (2006). “Hierarchical approach to production scheduling in make-to-order assembly”, International Journal of Production Research, Vol. 44, No. 4, PP. 801–830.
5
6. Omar, M. K. and Teo, S. C. (2007). “Hierarchical production planning and scheduling in a multi-product, batch process environment”, International Journal of Production Research, Vol. 45, No. 5, PP. 1029–1047.
6
7. Ebadian, M., Rabbani M., Torabi, S. A. and Jolai, F. (2009). “Hierarchical production planning and scheduling in make-to-order environments: reaching short and reliable delivery dates”, Internationl Journal of Production Research, Vol. 47, No. 20, PP. 5761–5789.
7
8. Bang, J. Y. J. and Kim, Y. D. Y. (2010). “Hierarchical production planning for semiconductor wafer fabrication based on linear programming and discrete event simulation,” IEEE Transactions on Automation Science & Engineering., Vol. 7, No. 2, PP. 326–336.
8
9. Mohammadi, M., Fatemi Ghomi, S. M. T., Karimi, B. and Torabi, S. A. (2010). “Rolling-horizon and fix-and-relax heuristics for the multi-product multi-level capacitated lot-sizing problem with sequence-dependent setups”, Journal of Intelligent Manufacturing, Vol. 21, No. 4, PP. 501–510.
9
10. Mohammadi, M. (2010). “Integrating lot sizing, loading, and scheduling decisions in flexible flow shops”, International Journal of Advanced Manufacturing Technology, Vol. 50, No. 9, PP. 1165–1174.
10
11. Kwak, I. S. and Jeong, I. J. (2011). “A hierarchical approach for the capacitated lot-sizing and scheduling problem with a special structure of sequence-dependent setups”, International Journal of Production Research, Vol. 49, No. ?24, PP. 7425–7439.
11
12. Camargo V. C. B., Toledo, F. M. B. and Almada Lobo, B. (2012). “Three time-based scale formulations for the two-stage lot sizing and scheduling in process industries”, Journal of the Operational Research Society, Vol. ?63, No. 11, PP. 1613–1630.
12
13. Seeanner, F. and Meyr, H. (2013). “Multi-stage simultaneous lot-sizing and scheduling for flow line production”, OR Spectrum, Vol. 35, No. 1, PP. 33–73.
13
14. Sereshti, N. and Bijari, M. (2013). “Profit maximization in simultaneous lot-sizing and scheduling Problem”, Applied Mathematical Modelling, Vol. 37, No. 23, PP. 9516–9523.
14
15. Babaei, M., Mohammadi, M. and Fatemi Ghomi, S. M. T. (2014). “A genetic algorithm for the simultaneous lot sizing and scheduling problem in capacitated flow shop with complex setups and backlogging”, International Journal of Advanced Manufacturing Technology, Vol. 70, No. 1, PP. 125–134.
15
16. Guimaraes, L., Klabjan, D. and Almada Lobo, B. (2014). “Modeling lot sizing and scheduling problems with sequence dependent setups”, European Journal of Operational Research, Vol. 239, No. 3, PP. 644–662.
16
17. Merce, C. and Fontan, G. (2003). “MIP-based heuristics for capacitated lot sizing problems”, International Journal of Production Economic, Vol. 41, No. 2, PP. 97–111.
17
ORIGINAL_ARTICLE
Location-Routing Problems: A Review of Concepts, Models, Methods and Research Gaps
A location-routing problem is a kind of location problem with the routing aspects. Although the basic idea of simultaneously solving the two problems started on 1961, and it has been done a lot of researches on this issue, but a comprehensive review of the problem literature in this paper, has identified research gaps, which indicates the potentiality of this problem in new studies. This paper surveys 303 related published researches. in which the large number of survey focuses on the location-routing problem in different periods, in this research, based on a comprehensive review of the problem definition, it is studied the different aspects and indexes, type of LRPs, type of objectives, categories of LRPs and solution methods with the authors’ proposed reforms. Finally, research gaps and recommendations for future studies are explained.
https://aie.ut.ac.ir/article_62214_bcec3390ae6b4060671a16ab75e135ce.pdf
2017-06-22
223
250
10.22059/jieng.2017.62214
Depot
Location-routing problem
Vehicles
Atefeh
Kahfi-Ardakani
atefehkahfi2009@gmail.com
1
Faculty of Industrial Engineering, Payame Noor University, Tehran, Iran
AUTHOR
Seyed Mohammad
Seyyed-Hosseini
seyedhosseini@iust.ac.ir
2
Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
AUTHOR
Reza
Tavakkoli-Moghaddam
tavakoli@ut.ac.ir
3
Faculty of Engineering, University of Tehran, Iran
LEAD_AUTHOR
1- Weber, A. (1962). Theory of the Location of Industries. C. J. Friedrich (Ed.). Chicago, Ill, USA: University of Chicago Press.
1
2- Lin, C., Choy, K.L., Ho, G.T.S., Chung, S.H. and Lam, H. Y. (2014). “Survey of Green Vehicle Routing Problem: Past and future trends”, Expert System with Application, Vol. 41, No. 4, PP. 1118–1138.
2
3- Montoya-Torres, J.R., Franco, J.L., Isaza, S. N., Jiménez, H.F. and Herazo-Padilla, N., (2015). “A literature review on the vehicle routing problem with multiple depots”, Computers & Industrial Engineering, Vol. 79, No. 1, PP. 115–129.
3
4- Lahyani, R., Khemakhem, M., Semet, F., (2015). “Rich vehicle routing problems: From a taxonomy to a definition” European Journal of Operational Research, Vol. 241, No. 1, PP. 1–14.
4
5- Drexl, M., Schneider, M. (2013). A survey of location-routing problems, Technical Report LM-2013-03, Chair of Logistics Management, Gutenberg School of Management & Economics, Johannes Gutenberg Uni., Mainz.
5
6- Prodhon, C., Prins, C., (2014). “A survey of recent Research on location-routing problems”, European Journal of Operational Research, Vol. 238, No. 1, PP. 1–17.
6
7- Min, H., Jayaraman, V., Srivastava, R., (1998). “Combined location-routing problems: a synthesis”, future Research Dir. European Journal of Operational Research, Vol. 108, No. 1, PP. 1–15.
7
8- Nagy, G., Salhi, S. (2007). “Location-routing: Issues, models and methods”, European Journal of Operational Research, Vol. 177, No.12, PP. 649–672.
8
9- Lopes, R.B., Ferreira, C., Santos, B.S., Barreto, S., (2013), “A taxonomical analysis, current methods and objectives on location-routing problems”, International Transactions in Operational Research, Vol. 20, No. 6, PP. 795–822.
9
10- Boventer, V., (1961). “The relationship between Transportation costs and location rent in Transportation problems”, Journal of Regional Science, Vol. 2, PP. 27-40.
10
11- Lawrence, R.M., Pengilly, P.J., (1969). “The number, location of depots required for handling products for distribution to retail stores in south-east England”, Operational Research Quarterly, Vol. 20, No. 1, PP. 23–32.
11
12- Tapiero, C.S., (1971). “Transaction-location-allocation problems over time”, Journal of Regional Science, Vol. 2, No. 3, PP. 377-384.
12
13- Chan, A.W., Francis, R.L. (1976). “A round-trip location problem on a tree graph”, Transportation Science, Vol. 10, No. 1, PP. 35–51.
13
14- Burness, R.C., White, J.A., (1976). “The traveling salesman location problem”, Transportation Science, Vol. 10, No. 4, PP. 348–360.
14
15- Jacobsen, S.K., Madsen, O.B.G., (1978). “On the location of transfer points in a two-level newspaper delivery system-A case study”, The International Symposium on Locational Decisions, Ban, Alberta, Canada.
15
16- Jacobsen, S.K., Madsen, O.B.G, (1980). “A comparative study of heuristics for a two-level routing-location problem”, European Journal of Operational Research, Vol. 5, No. 6, PP. 378–387.
16
17- Laporte, G., Nobert, Y. (1981). “An exact algorithm for minimizing routing and operating costs in depot location”, European Journal of Operational Research, Vol. 6, No. 2, PP. 224–226.
17
18- Perl, J., Daskin, M. (1984). “A unified warehouse location-routing methodology”, Journal of Business Logistics, Vol. 5, No. 1, PP. 92–111.
18
19- Drezner, Z., Steiner, G., Wesolowsky, G.O., (1985). “One-facility location with rectilinear tour distances”, Naval Research Logistics Quarterly., Vol. 32, No. 3, PP. 391–405.
19
20- Maze, T.H., Khasnabis, S., (1985). “Bus garage location planning with dynamic vehicle assignments: A methodology”, Transportation Research B, Vol. 19, No. 1, PP. 1–13.
20
21- Labbe, M., Laporte, G., (1986). “Maximizing user convenience, postal service efficiency in post box location”. Belgian Journal of Operational Research, Statistics, Computer Science, Vol. 26, No. 2, PP. 21–35.
21
22- Laporte, G. (1988). “Location-routing problems”, in B. Golden and A. Assad (Eds.), Vehicle routing: Methods and studies, North-Holland, Amsterdam, PP. 163–198.
22
23- Levy, L., Bodin, L., (1989). “The arc oriented location routing problem”, INFOR27, Vol. 1, No. 1, PP. 74–94.
23
24- Nambiar, J.M., Gelders, L.F., Van Wassenhove, L.N., (1989). “Plant location, vehicle routing in the Malaysian rubber smallholder sector: a case study”, European Journal of Operational Research, Vol. 38, No. 1, PP. 14–26.
24
25- Zografos, K.G., Samara, S., (1989). “A combined location-routing model for hazardous waste Transportation and disposal”, Transportation Research Record,Vol. 1245, No. 1, PP. 52–59.
25
26- Nagy, G., (1996). “Heuristic Methods for the Many-to-Many Location-Routing Problem”, PhD dissertation, University of Birmingham.
26
27- Ghiani, G., Laporte, G., (1999). “Eulerian location problems”, Networks., Vol. 34, No. 4, PP. 291–302.
27
28- Liu, S., Lee, S., (2003). “A two-phase heuristic method for the multi-depot location routing problem taking inventory control decisions into consideration”, International Journal of Advanced Manufacturing Technology, Vol. 22, No. 11–12, PP. 941–950.
28
29- Wasner, M., Zapfel, G., (2004). “An integrated multi-depot hub-location vehicle routing model for network planning of parcel service”, International Journal of Production Economics, Vol. 90, No. 3, PP. 403–419.
29
30- Ambrosino, D., Scutella, M.G., (2005). “Distribution network design: new problems”, related models. European Journal of Operational Research, Vol. 165, No. 3, PP. 610–624.
30
31- Schwardt, M., Dethloff, J., (2005). “Solving a continuous location-routing problem by use of a self-organising map”, International Journal of Physical Distribution & Logistics Management, Vol. 35, No. 6, PP. 390–408.
31
32- Glicksman, H., Penn, M. (2008). “Approximation algorithms for group prize-collecting and location-routing problems”, Discrete Applied Mathematics, Vol. 156, No. 17, PP. 3238–3247.
32
33- Prodhon, C., (2008). “A metaheuristic for the periodic location-routing problem”, In J. Kalcsics, S. Nickel, Operational Research Proceedings 2007, 159–164. Springer.
33
34- Mirzaei, Sh., Krishnan, K., (2012), “Location Routing Problem with Time Dependent Travel Times”, Journal of Supply Chain and Operational Management, Vol. 10, No. 1, PP. 87-106.
34
35- Karaoglan, I., Altiparmak, F., Kara, I., Dengiz, B. (2011). “A branch and cut algorithm for the location-routing problem with simultaneous pickup and delivery”, European Journal of Operational Research, Vol. 211, No. 2, PP. 318–332.
35
36- Zarandi, M.H.F., Hemmati, A., Davari, S. (2011). “The multi-depot capacitated location-routing problem with fuzzy travel times”, Expert System with Application, Vol. 38, No. 8, PP. 10075–10084.
36
37- Xuefeng, W., 2012, “An location-routing problem with simultaneous pickup and delivery in urban-rural dual-directions logistics network”, Proceedings of the 2012 2nd ICCIA 2012, PP. 1645-1649.
37
38- Harks, T., Konig, F.G., Matuschke, J. (2013). “Approximation algorithms for capacitated location routing”, Transportation Science, Vol. 47, No. 1, PP. 3–22.
38
39- Ahmadi-Javid, A., Seddighi, A. (2013). “A location-routing problem with disruption risk”, Transportation Research Part E: Logistics and Transportation Review, Vol. 53, No. 1, PP. 63–82.
39
40- Ahmad, H., Hamzah, P., Yasin, Z. A. Md, Radiah, S. S., (2014). “Location Routing Inventory Problem with Transshipment (LRIP-T)”, Proceedings of the 2014 International Conference on Industrial Engineering and Operational Management, Bali, Indonesia, January 7- 9, PP. 1595-1605.
40
41- Yu, V.F., Lin, S.Y., (2015), “A simulated annealing heuristic for the open location-routing problem”, Computer & Operational Research, Vol. 62, No. ???, PP. 184–196.
41
42- Karaoglan, I., Altiparmak, F., (2015). “A memetic algorithm for the capacitated location-routing Problem with mixed backhauls”, Computer & Operational Research, Vol. 55, No. 2, PP. 200–216.
42
43- Huang, S. H. (2015). “Solving the multi-compartment capacitated location routing problem with pickup–delivery routes and stochastic demands”, Computers & Industrial Engineering, Vol. 87, No. 1, PP. 104-113.
43
44- Moshref-Javadi, M., Lee, S. (2016). “The Latency Location-Routing Problem”, European Journal of Operational Research, Vol. 255, No. 2, PP. 604-619.
44
45- Toro, E.M., Franco, J.F., Echeverri, M.G., Guimarães, F.G., Rendón, R.A.G., (2017). “Green open location-routing problem considering economic and environmental costs”, International Journal of Industrial Engineering Computers, Vol. 8, No. 2, PP. 203–216.
45
46- Drexl, M., Schneider, M. (2015). “A survey of variants and extensions of the location-routing problem”, European Journal of Operational Research, Vol. 241, No. 2, PP. 283-308.
46
47- Drexl, M., Schneider, M. (2014). “A survey of the standard location-routing problem”, Working paper, Logistics Planning and Information Systems, TU Darmstadt, Germany.
47
48- Liu, T., Jiang, Z., Chen, F., Liu, R., Liu, S., (2008). “Combined Location-Arc Routing Problems: Asurvey and Suggestions for Future Research”, Service Operational and Logistics, and Informatics, 2008.
48
49- Srivastava, R., (1986). “Algorithms for Solving the Location Routing Problem”, PhD dissertation, Ohio State University.
49
50- Balakrishnan, A., Ward, J., Wong, R. (1987). “Integrated facility location and vehicle routing models: Recent work and future prospects”, American Journal of Mathematics and Management Science, Vol. 7, No. (1-2), PP. 35–61.
50
51- Namazian, A., (2009). “Models and methods for routing location.” Ms thesis, University ghom.
51
52- Jalili Bolhasani, S., Karimi, H., Satac, M., (2012). “Evaluate and compare different methods for solve the location routing problem”, 2th National Conference on Industrial Engineering & system, Islamic Azad University of Najafabad, Iran.
52
53- Delavari, M., (2015), A mathematical model for multi-objective location routing problem for Landfill and recovery of hospital waste under environmental considerations and uncertainty, University of Tehran.
53
54- Salhi, S., Nagy, G., (1999). “Consistency and robustness in location-routing”, Studies in Locational Analysis, Vol. 13, No. 1, PP. 3–19.
54
55- Jouzdani, J., Fathian, M., (2014). “A linear MmTSP formulation of robust location-routing problem: a dairy products supply chain case study”, International JJournal Applied Decision Science, Vol. 7, No. 3, PP. 327-342.
55
56- Stowers, C.L., Palekar, U.S., (1993a). “Location models with routing considerations for a single obnoxious facility”, Transportation Science, Vol. 27, No. 4, PP. 350–362.
56
57- Boffey, B., Karkazis, J., (1995). “Location, routing and the environment”, In: Drezner, Z. (Ed.), Facility Location: A Survey of Applications and Methods. Springer, New York, PP. 453–466.
57
58- Berger, R., (1997). “Location-routing models for distribution system design”, PhD dissertation, Northwestern University.
58
59- Perl, J., (1983). “A unified warehouse location-routing analysis”, Ph.D. Dissertation, Department of Civil Engineering, Northwestern University, Evanston, Illinois.
59
60- Salhi, S., (1987). “The Integration of Routing into the Location Allocation and Vehicle Fleet Composition Problems”, PhD dissertation, Lancaster University.
60
61- Laporte, G., Nobert, Y., Taillefer, S., (1988). “Solving a family of multi-depot vehicle routing, location-routing problems”, Transportation Science, Vol. 22, No. 3, PP. 161–172.
61
62- Murty, K.G., Djang, P.A., (1999). “The U.S. army National Guard’s mobile training simulators location, routing problem”, Operational Research, Vol. 47, No. 2, PP. 175–182.
62
63- Lin, C.K.Y, Chow, C.K., Chen, A., (2002). “A location-routing-loading problem for bill delivery services”, Computer & Industrial Engineering, Vol. 43, No. 1–2, PP. 5–25.
63
64- Barreto, S. (2004). “Analysis and modelling of location-routing problems”, Ph.D. thesis, University of Aveiro, Aveiro, Portugal. (In Portuguese)
64
65- Tham, W.C., (2005). “Depot location-routing models based on a real supply chain network”, PhD dissertation, Lancaster University.
65
66- Prodhon, C., (2006). “Le Problème de Localisation-Routage (The location-routing problem)”, Ph.D. thesis, Troyes University of Technology, France. (In French)
66
67- Berger, R. T., Coullard, C. R., Daskin, M. S. (2007). “Location-routing problems with distance constraints”, Transportation Science, Vol. 41, No. 1, PP. 29–43.
67
68- Özyurt, Z., Aksen, D., (2007). “Solving the multi-depot location-routing problem with Lagrangian relaxation”, in E. Baker et.al., Extending the Horizons: Advances in Computing, Optimization, and Decision Technologies, of Operational Research/Computer Science Interfaces, Springer., Vol. 37, No. 1, PP. 125–144.
68
69- Sterle, C. (2010). “Location-routing models and methods for freight distribution and infomobility in city logistics”, Technical report CIRRELT-2010-38, CIRRELT, Canada.
69
70- Carnes, T., Shmoys, D.B. (2011). “Primal-dual schema and Lagrangian relaxation for the k-location-routing problem”, In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (pp. 99-110). Springer Berlin Heidelberg.
70
71- Catanzaro, D., Gourdin, E., Labbe, M., Ozsoy, F.A., (2011). “A branch-and-cut algorithm for the partitioning-hub location routing problem”, Computer & Operational Research, Vol. 38, No. 2, PP. 539–549.
71
72- Hua-Li, S., Xun-Qing, W., Yao-Feng, X. (2012). “A bi-level programming model for a multi-facility location-routing problem in urban emergency system”, Engineering Education and Management, Vol. 111 of the series Lecture Notes in Electrical Engineering, 75-80.
72
73- Boudahri, F., Aggoune-Mtalaa, W., Bennekrouf, M., Sari, Z. (2013). “Application of a clustering based location-routing model to a real agri-food supply chain redesign”, In N.T. Nguyen et.al., Advanced methods for computational collective intelligence, Springer, PP. 323–331.
73
74- Ceselli, A., Righini, G., Tresoldi, E., (2014). “Combined location and routing problems for drug distribution”, Discrete Applied Mathematics, Vol. 165, No. 1, PP. 130–145.
74
75- Yıldız, B., Arslan, O., Karaşan, O. E., (2016). “A branch and price approach for routing and refueling station location model”, European Journal of Operational Research, Vol. 248, No. 3, PP. 815–826.
75
76- Alinaghian, M., Behrozi, M., (2006). “A mathematical programming models for locating warehouses in vehicle routing a production unit with solving method”, 2th National Conference on Logistics & Supply Chain, Iran Logistics Society, Tehran, Iran.
76
77- Tavakoli-Moghaddam, R., Haidar, M., Mousavi, S.A., (2008) A model of location routing problems with allocation of a product. 6th International Conference on Industrial Engineering, Iran Institute of Industrial Engineering.
77
78- Setak, M., Azizi, V., Karimi, H., (2013), “Location routing problem with simultaneous pickup and delivery and split Loads with soft time window”, 10th International Conference on Industrial Engineering, Iran Institute of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran.
78
79- Mazahery, S., Homayouni, S.M., (2014). Modeling location-routing problem for Cross- warehouses in waste collection network. 2th National Conference on Industrial Engineering & Sustainable Management (IESM’14), 15-16 Oct, Islamic Azad University, Isfahan, Iran.
79
80- Maranzana, F. (1964). “On the location of supply points to minimize transport costs”, Operational Research Quarterly, Vol. 15, No. 1, PP. 261–270.
80
81- Watson-Gandy, C.D.T., Dohrn, P.J., (1973). “Depot location with van salesmen–a practical approach”, Omega, Vol. 1, No. 3, PP. 321–329.
81
82- Or, I., Pierskalla, W.P., (1979). “A Transportation location-allocation model for regional blood banking”, AIIE Transportation, Vol. 11, No. 2, PP. 86–95.
82
83- Nambiar, J.M., Gelders, L.F., Van Wassenhove, L.N., (1981). “A large scale location-allocation problem in the natural rubber industry”, European Journal of Operational Research, Vol. 6, No. 2, PP. 183–189.
83
84- Srivastava, R., Benton, W.C., (1990). “The location-routing problem: considerations in physical distribution system design”, Computer & Operational Research, Vol. 17, No. 5, PP. 427–435.
84
85- Min, H., (1996). “Consolidation terminal location-allocation, consolidated routing problems”, Journal of Business Logistics, Vol. 17, No. 2, PP. 235–263.
85
86- Nagy, G., Salhi, S., (1996a). “Nested heuristic methods for the location-routeing problem”, Journal of the Operational Research Society, Vol. 47, No. 9, PP. 1166–1174.
86
87- Nagy, G., Salhi, S., (1996b). “A nested location-routing heuristic using route length estimation”, Studies in Locational Analysis, Vol. 10, No. ???, PP. 109–127.
87
88- Salhi, S., Fraser, M., (1996). “An integrated heuristic approach for the combined location vehicle fleet mix problem”, Studies in Locational Analysis, Vol. 8, No. 1, PP. 3–21.
88
89- Albareda-Sambola, M., (2003). “Models and Algorithms for Location-Routing and Related Problems”, PhD dissertation, Catalonia Polytechnic University.
89
90- Albareda-Sambola, M., Díaz, J. A., Fernández, E. (2005). “A compact model and tight bounds for a combined location-routing problem”, Computer & Operational Research, Vol. 32, No. 3, PP. 407–428.
90
91- Singh, N., Shah, J., 2004. “Managing tendu patta leaf logistics: an integrated approach”, International Transportation in Operational Research, Vol. 11, No. 6, PP. 683–699.
91
92- Chan, Y, Baker, S. (2005). “The multiple depots, multiple traveling salesmen facility-location problem: Vehicle range, service frequency, and heuristic implementations”, Mathematics & Computer Modelling, Vol. 41, No. 8-9, PP. 1035–1053.
92
93- Melechovsky, J., Prins, C., Wolfler Calvo, R., (2005). “A metaheuristic to solve a location-routing problem with non-linear costs”, Journal of Heuristics, Vol. 11, No. 5, PP. 375–391.
93
94- Wang, X., Sun, X., Fang, Y., (2005). “A two-phase hybrid heuristic search approach to the location-routing problem”, IEEE International Conference on Systems, Man and Cybernetics, Vol. 4, No. 1, PP. 3338–3343.
94
95- Lashine, S.H., Fattouh, M., Issa, A., (2006). “Location/allocation, routing decisions in supply chain network design”, Journal of Modelling in Management, Vol. 1, No. 2, PP. 173–183.
95
96- Chen, C., Ting, C. (2007). “A hybrid Lagrangian heuristic/simulated annealing algorithm for the multi-depot location routing problem”, Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 6, No. 1, PP. 137–150.
96
97- Aksen, D., Altinkemer, K. (2008). “A location-routing problem for the conversion to the click-and-mortar retailing: the static case”, European Journal of Operational Research, Vol. 186, No. 2, PP. 554–575.
97
98- Ambrosino, D., Sciomachen, A., Scutellà, M.G. (2009). “A heuristic based on multiexchange techniques for a regional fleet assignment location-routing problem”, Computer Operational Research, Vol. 36, No. 2, PP. 442–460.
98
99- Prodhon, C., (2009a). “An ELS×path relinking hybrid for the periodic location-routing problem”, In M. Blesa et. al..6th International workshop of lecture notes in Computer Science, Hybrid metaheuristics 5818: 15–29. Springer.
99
100- Schittekat, P., Sorensen, K., (2009). “Supporting 3PL decisions in the automotive industry by generating diverse solutions to a large-scale location-routing problem”, Operational Research, Vol. 57, No. 5, PP. 1058–1067.
100
101- Derbel, H., Jarboui, B., Hanafi, S., Chabchoub, H. (2010). “An iterated local search for solving a location-routing problem”, Electronic Notes in Discrete Mathematics, Vol. 36, No. 1, PP. 875–882.
101
102- Pirkwieser, S., Raidl, G. R. (2010). “Variable neighborhood search coupled with ILPbased very large neighborhood searches for the (periodic) location-routing problem”, Hybrid Metaheuristics, series Lecture Notes in Computer Science 6373, PP. 174-189.
102
103- Prodhon, C. (2011). “A hybrid evolutionary algorithm for the periodic location-routing problem”, European Journal of Operational Research, Vol. 210, No. 2, PP. 204–212.
103
104- Rath, S., Gutjahr, W.J., (2011). “A math-heuristic for the warehouse location–routing problem in disaster relief”, Computer and Operational Research, Vol. 42, No. ???, PP. 25–39
104
105- Ahn, J., de Weck, O., Geng, Y., Klabjan, D. (2012). “Column generation based heuristics for a generalized location routing problem with profits arising in space exploration”, European Journal of Operational Research, Vol. 223, No. 1, PP. 47–59.
105
106- Albareda-Sambola, M., Fernandez, E., Nickel, S. (2012). “Multi-period location-routing with decoupled time scales”, European Journal of Operational Research, Vol. 217, No. 1, PP. 248–258.
106
107- Xu, Z., Xu, D., Zhu, W., (2012). “Approximation results for a min–max location-routing problem”, Discrete Applied Mathematics, Vol. 160, No. 3, PP. 306–320.
107
108- Alvim, A., Taillard, E. (2013). “POPMUSIC for the world location-routing problem”, Eur J. on Transportation and Logistics, Vol. 2, No. 3, PP. 231–254.
108
109- Hemmelmayr, V.C. (2015). “Sequential and parallel large neighborhood search algorithms for the periodic location routing problem”, European Journal of Operational Research, Vol. 243, No. 1, PP. 52-60.
109
110- Koç, Ç., Bektaş, T., Jabalib, O., Laporte, G., (2016). “The fleet size and mix location-routing problem with time windows: Formulations and a heuristic algorithm”, European Journal of Operational Research, Vol. 248, No. 1, PP. 33–51.
110
111- Badiozaman, M.M., salmasi, N., (2008), “An approximate solution for a distribution network model of location-routing problem”, 6th International Conference on Industrial Engineering, Tehran, Iran.
111
112- Prodhon, C., Prins, C., (2008). “A memetic algorithm with population management (MAPM) for the periodic location-routing problem”, In Blesa et al. (Vol. Eds.). 5th International workshop, lecture notes in Computer Science, Hybrid metaheuristics, 5296, 43–57. Springer.
112
113- Prodhon, C., (2009b). “An evolutionary algorithm for the periodic location-routing problem”, In Odysseus 2009- Fourth International Workshop on Freight Transportation and Logistics.
113
114- Derbel, H., Jarboui, B., Hanafi, S., Chabchoub, H., (2012). “Genetic algorithm with iterated local search for solving a location-routing problem”, Expert Systems with Application, Vol. 39, No. 3, PP. 2865–2871.
114
115- Stenger, A., Schneider, M., Schwind, M., Vigo, D. (2012). “Location routing for small package shippers with subcontracting options”, International Journal of Production Economics, Vol. 140, No. 2, PP. 702–712.
115
116- Linfati, R., Escobar, J.W., Gatica, G., (2014). “A metaheuristic algorithm for the location routing problem with heterogeneous fleet”, IngIneering CIENC., Vol. 10, No. 19, PP. 55–76, enero-junio.
116
117- Meiyi, W., Lean, Y., Xiang, L., (2014). “Credibilistic Location-Routing Model for Hazardous Materials Transaction”, International Journal of Intelligent System, Vol. 00, No. 1, PP. 1–17.
117
118- Razavi, M., Sokakhyan, M., Ziaraty, K., (2012). “Ant Colony Algorithm for location routing problem with multiple warehouses and assumption of allocation multiple paths to each vehicle”, Journal of Industrial Management, Vol. 3, No. 6, PP. 17-38
118
119- Azizi, V., (2013). “Model of location routing problem simultaneous and cut pickup and delivery”, MS thesis, K. N. Toosi University of Technology.
119
120- Lin, C.K.Y., Kwok, R.C.W., (2006). “Multi-objective metaheuristics for a location-routing problem with multiple use of vehicles on real data, simulated data”, European Journal of Operational Research, Vol.175, No. 3, PP. 1833–1849.
120
121- Mahmoudabadi, A., Seyedhosseini, S. M., (2013), “Developing a Bi-level Objective Model of Risk-Cost Trade-off for Solving Locating-Routing Problem in Transaction of Hazardous Material”, International Journal of Transportation Engineering, Vol. 1, No. 3, PP. 173-182.
121
122- Johnson, M.P., Gorr, W.L., Roehrig, S.F., (2002). “Location/allocation/routing for home-delivered meals provision”, International Journal of Industrial Engineering, Vol. 9, No. 1, PP. 45–56.
122
123- Caballero, R., Gonzalez, M., Guerrero, F.M., Molina, J., Paralera, C. (2007). “Solving a multiobjective location routing problem with a metaheuristic based on tabu search. Application to a real case in Andalusia”, European Journal of Operational Research, Vol. 177, No. 3, PP. 1751–1763.
123
124- Tavakkoli-Moghaddam, R., Makui, A., Mazloomi, Z. (2010). “A new integrated Mathematics model for a bi-objective multi-depot location-routing problem solved by a multi-objective scatter search algorithm”, Journal of Manufacturing System, Vol. 29, No. 2-3, PP. 111–119.
124
125- Lopes, R.B., Barreto, S., Ferreira, C., Santos, B.S., (2008). “A decision-support tool for a capacitated location-routing problem”, Decision Support System, Vol. 46, No. 1, PP. 366–375.
125
126- Laporte, G., Nobert, Y., Arpin, D. (1984). Capacitated location-routing problems. Paper presented at The Third International Symposium on Locational Decisions, Boston, Massachusetts.
126
127- Laporte, G., Nobert, Y., Arpin, D., (1986). “An exact algorithm for solving a capacitated location-routing problem”, Annals of Operational Research, Vol. 6, No. 9, PP. 293–310.
127
128- Chien, T.W., (1993). “Heuristic procedures for practical-sized uncapacitated location-capacitated routing problems”, Decision Science, Vol. 24, No. 5, PP. 995–1021.
128
129- Prins, C., Prodhon, C., Wolfler Calvo, R. (2004). “Nouveaux algorithmes pour le problème de localisation et routage sous contraintes de capacité”, In A. Dolgui and S. Dauzère-Pérèz (eds), MOSIM’ 04, 2, PP. 1115–1122.
129
130- Akca, Z., Berger, R.T., Ralphs, T.K. (2009). “A branch-and-price algorithm for combined location and routing problems under capacity restrictions”, InOperations research and cyber-infrastructure (pp. 309-330). Springer US.
130
131- Baldacci, R., Mingozzi, A., Wolfler-C., R. (2011). “An exact method for the capacitated location-routing problem”, Operational Research, Vol. 59, No. 5, PP. 1284–1296.
131
132- Belenguer, J.M., Benavent, E., Prins, C., Prodhon, C., Wolfler Calvo, R. (2011). “A branch-and-cut method for the capacitated location-routing problem”, Computer Operational Research, Vol. 38, No. 6, PP. 931–941.
132
133- Contardo, C., Cordeau, J.F., Gendron, B. (2013a). “A computational comparison of flow formulations for the capacitated location-routing problem”, Discrete Optimization, Vol. 10, No. 4, PP. 263-295.
133
134- Contardo, C., Cordeau, J.F, Gendron, B. (2013b). “An exact algorithm based on cut-and-column generation for the capacitated location-routing problem”, INFORMS J. on Computing.
134
135- Contardo, C., Cordeau, J.F., Gendron,B. (2013c). “A branch-and-cut-and-price algorithm for the capacitated location-routing problem”, CIRRELT.
135
136- Irannezhad, S., Jalili Bolhasani, S., Rezazadeh, H., (2012). “The multi product locating-routing problem with constraints on capacity and maximum time of vehicle availability vehicle”, Journal of Supply Chain Management, Vol. 38, No. 1, PP. 26-31.
136
137- Perl, J., Daskin, M.S. (1985). “A warehouse location-routing problem”, Transportation Research B, Vol. 19B, No. 5, PP. 381-396.
137
138- Srisvastava. R., (1993). “Alternate solution procedures for the location-routing problem”, Omega, Vol. 21, No.4, PP. 497-506.
138
139- Hansen, P., Hegedahl, B., Hjortkjr, S., Obel, B. (1994). “A heuristic solution to the warehouse location-routing problem”, European Journal of Operational Research, Vol. 76, No. 1, PP. 111–127.
139
140- Su, C.T., (1998). “Locations, vehicle routing designs of physical distribution systems”, Production Planning & Control, Vol. 9, No. 7, PP. 650–659.
140
141- Wu, T.H., Low, C., Bai, J.W. (2002). “Heuristic solutions to multi-depot location-routing problems”, Computer & Operational Research, Vol. 29, No. 10, PP. 1393–1415.
141
142- Barreto, S., Ferreira, C., Paixao, J., Santos, B. (2007). “Using clustering analysis in a capacitated location-routing problem”, European Journal of Operational Research, Vol. 179, No. 3, PP. 968-977.
142
143- Guerra, L., Murino, T., Romano, E., (2007). “A heuristic algorithm for the constrained location–routing problem”, International Journal of System Application Engineering & Development, Vol. 1, No. 4, PP. 146–154.
143
144- Duhamel, C., Lacomme, P., Prins, C., Prodhon, C. (2008). “A memetic approach for the capacitated location routing problem”, International Workshop on Metaheuristics for Logistics and Vehicle Routing (EU/MEeting 2008).
144
145- Lam, M., Mittenthal, J., Gray, B., (2009). “The impact of stopping rules on hierarchical capacitated clustering in location routing problems”, Academy of Information and Management Science Journal, Vol. 12, No. 1, PP. 13-28.
145
146- Sahraeian, R., Nadizadeh, A. (2009). “Using greedy clustering method to solve capacitated location-routing problem”, Direccion y Organ., Vol. 39, No. 17, PP. 79–85.
146
147- Derbel, H., Jarboui, B., Chabchoub, B., Hanafi, S., Mladenovic, N. (2011). “A variable neighborhood search for the capacitated location-routing problem”, LOGISTIQUA, 4th International Conference on logistics, PP. 514-519.
147
148- Jabal-Ameli, M., Aryanezhad, M., Ghaffari-Nasab, N. (2011). “A variable neighborhood descent based heuristic to solve the capacitated location routing problem”, International Journal of Industrial Engineering Comput., Vol. 2, No. 1, PP. 141–154.
148
149- Jokar, A., Sahraeian, R. (2011). “An iterative two phase search based heuristic to solve the capacitated location-routing problem”, Australian Journal of Basic and Applied Science, Vol. 5, No. 12, PP. 1613–1621.
149
150- Nadizadeh, A., Sahraeian, R., Zadeh, A.Homayouni, S. (2011). “Using greedy clustering method to solve capacitated location-routing problem”, African Journal of Business Management, Vol. 5, No. 21, PP. 8470–8477.
150
151- Jokar, A., Sahraeian, R. (2012). “A heuristic based approach to solve a capacitated location-routing problem”, Journal of Management and Sustainability, Vol. 2, No. 2, PP. 219–226.
151
152- Contardo, C., Cordeau, J.F., Gendron, B. (2013d). “A GRASP +ILP-based metaheuristic for the capacitated location-routing problem”, Journal of Heuristics, Vol. 20, No. 1, PP. 1-38.
152
153- Escobar, J.W., Linfati, R., Toth, P., (2013). “A two-phase hybrid heuristic algorithm for the capacitated location-routing problem”, Computer & Operational Research, Vol. 40, No. 1, PP. 70–79.
153
154- Lam, M., Mittenthal, J. (2013). “Capacitated hierarchical clustering heuristic for multi depot location routing problems”, International Journal of Logistics Research and Applications 16(5), PP. 433–444.
154
155- Zare Mehrjerdi, Y., Nadizadeh, A. (2013). “Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands”, European Journal of Operational Research, Vol. 229, No. 1, PP. 75–84.
155
156- Irannezhad, S., Ahmady, A., (2012). “Heuristic algorithm based on clustering for solving capacity location-routing problem using neural network of self organization map”, 10th International Conference on Industrial Engineering, Tehran, Iran.
156
157- Tuzun, D., Burke, L.I., (1999). “A two-phase tabu search approach to the location routing problem”, European Journal of Operational Research, Vol. 116, No. 1, PP. 87–99.
157
158- Bouhafs, L., Hajjam, A., Koukam, A. (2006). “A combination of simulated annealing and ant colony system for the capacitated location-routing problem”, In Gabrys et. al., Knowledge-Based Intelligent Information and Engineering Systems, Vol. 4251 of Lecture Notes in Computer Science, Springer, PP. 409–416.
158
159- Prins, C., Prodhon, C., Wolfler Calvo, R., (2006a). “Solving the capacitated location-routing problem by a GRASP complemented by a learning process, a path relinking”, 4OR4: A Quarterly Journal of Operations Research, Vol. 4, No. 3, 221–238.
159
160- Prins, C., Prodhon, C., Wolfler Calvo, R. (2006b). “A memetic algorithm with population management (MAPM) for the capacitated location-routing problem”, 16 Conference: Evolutionary Computation in Combinatorial Optimization”, 6th European Conference, EvoCOP 2006, Budapest, Hungary, April.
160
161- Prins, C., Prodhon, C., Ruiz, A., Soriano, P., Wolfler Calvo, R. (2007). “Solving the capacitated location-routing problem by a cooperative Lagrangean relaxation-granular tabu search heuristic”, Transportation Science, Vol. 41, No. 4, PP. 470–483.
161
162- Marinakis, Y., Marinaki, M. (2008a). “A bilevel genetic algorithm for a real life location routing problem”, International Journal of Logistics Research & Applications, Vol. 11, No. 1, PP. 49–65.
162
163- Marinakis, Y., Marinaki, M. (2008b). “A particle swarm optimization algorithm with path relinking for the location routing problem”, Journal of Mathematics Modelling and Algorithm, Vol. 7, No. 1, PP. 59–78.
163
164- Duhamel, C., Lacomme, P., Prins, C., Prodhon, C. (2010). “A GRASP+ELS approach for the capacitated location-routing problem”, Computer & Operational Research, Vol. 37, No. 11, PP. 1912–1923.
164
165- Yu, V.F., Lin, S.W., Lee, W., Ting, C.J., (2010). “A simulated annealing heuristic for the capacitated location routing problem”, Computer & Industrial Engineering, Vol. 58, No. 2, PP. 288–299.
165
166- Stenger, A., Schneider, M., Enz, S. (2011). “A hybrid GRASP×VNS algorithm with effective depot reduction mechanism for the capacitated location routing problem”, Technical report 01/2011, IT-based Logistics, Goethe University Frankfurt.
166
167- Golozari, F., Jafari, A., Amiri, M. (2013). “Application of a hybrid simulated annealing-mutation operator to solve fuzzy capacitated location-routing problem”, International Journal of Advanced Manufacturing Technology, Vol. 67, No. 5-8, PP. 1791–1807.
167
168- Jarboui, B., Derbel, H., Hanafi, S., Mladenovic, N., (2013). “Variable neighborhood search for location routing”, Computer & Operational Research, Vol. 40, No. 1, PP. 47–57.
168
169- Ting, C.J., Chen, C.H. (2013). “A multiple ant colony optimization algorithm for the capacitated location routing problem”, International Journal of Production Economics, Vol. 141, No. 1, PP. 34–44.
169
170- Zhang, Y., Qi, M., Lin, W.H., Miao, L., (2015). “A metaheuristic approach to the reliable location routing problem under disruptions”, Transportation Research Part E, Vol. 83, No. 1, PP. 90–110.
170
171- Mohammadi-Shad, A., Fattahi, P., (2011). “A hybrid heuristic algorithm for solving capacity locating-routing problem”, 2th International Conference & 4th National Conference of Supply Chain, Tehran, Iran.
171
172- Mohammadi-Shad, A., Fattahi, P., (2012). “A hybrid meta-heuristic method for capacity locating routing problem with hard time windows”, Journal of Industrial Engineering, Vol. 46, No. 2, PP. 219-223.
172
173- Ebadati, M., (2012). “Presented an algorithm for integrated location routing problem (compared with other iterative methods and hierarchical)”, MS thesis, Bu-Ali Sina University.
173
174- Setak, M., Azizi, V., Karimi, H., (2015), “Multi depots Capacitated Location-Routing Problem with Simultaneous Pickup and delivery and Split Loads: Formulation and heuristic methods”, Journal of Industrial Engineering Research in Production System, Vol. 2. No.4. PP. 67-81.
174
175- Ghaffari-Nasab, N., Jabalameli, M. S., Aryanezhad, M. B., Makui, A. (2012). “Modeling and solving the bi-objective capacitated location-routing problem with probabilistic travel times”, International Journal of Advanced Manufacturing Technology, Vol. 67, No. 9, PP.2007-2019.
175
176- Samaei, F., (2011). “Capacity location - routing problem with time window”, MS thesis, Shahed University.
176
177- Azizi, M., Javanshir, H., Proud, A.h., (1392). “A new mathematical model for Multi-Objective location routing problem and solving with efficient meta-heuristic algorithm”, 10th International Conference on Industrial Engineering, Tehran, Iran.
177
178- Cooper, L., (1972). “The Transaction-location problem”, Operational Research, Vol. 20, No. 1, PP. 94–108.
178
179- Cooper, L., (1978). “The stochastic Transaction-location problem”, Computer & Mathematics with Application, Vol. 4, No. 3, PP. 265–275.
179
180- Franca, P.M., Luna, H.P.L., (1982). “Solving stochastic Transaction-location problems by generalized Benders decomposition”, Transportation Science, Vol. 16, No. 2, PP. 113-126.
180
181- Hindi, K.S., Basta, T., (1994). “Computationally efficient solution of a multiproduct, two-stage distribution-location problem”, Journal of the Operational Research, Society, Vol. 45, No. 11, PP. 1316–1323.
181
182- Nema, A.K., Gupta, S.K., (1999). “Optimization of regional hazardous waste management systems: an improved formulation”, Waste Management, Vol. 19, No. 7–8, PP. 441–451.
182
183- Cappanera, P., Gallo, G., Maffioli, F., (2004). “Discrete facility location, routing of obnoxious activities”, Discrete Applied Mathematics, Vol. 133, No. 1–3, PP. 3–28.
183
184- Antunes, A.P., Teixeira, J.C., Coutinho, M.S., (2008). “Managing solid waste through discrete location analysis: a case study in central Portugal”, Journal of the Operational Research Society, Vol. 59, No. 8, PP. 1038–1046.
184
185- Klibi, W., Lasalle, F., Martel, A., Ichoua, S. (2010). “The stochastic multiperiod location Transaction problem”, Transportation Science, Vol. 44, No. 2, PP. 221–237.
185
186- Samanlioglu, F., (2013). “A multi-objective mathematic model for the industrial hazardous waste location-routing problem”, European Journal of Operational Research, Vol. 226, No. 2, PP. 332–340.
186
187- Cooper, L., (1976). “An efficient heuristic algorithm for the Transportation-location problem”, Journal of Regional Science, Vol.16, No. 3, PP. 309–315.
187
188- LeBlanc, L.J., (1977). “A heuristic approach for large scale discrete stochastic Transportation-location problems”, Computer & Mathematics with Application, Vol. 3, No. 2, PP. 87–94.
188
189- Lee, C. Y., (1993). “A heuristic approach for a stochastic Transportation-location problem with cross decomposition”, Information & Management Science, Vol. 4, No. 2, PP. 47-65.
189
190- Aykin, T., 1995. “The hub location-routing problem”, European Journal of Operational Research, Vol. 83, No. 1, PP. 200–219.
190
191- Averbakh, I., Berman, O., (2002). “Minmaxp-traveling salesmen location problems on a tree”, Annals of Operational Research, Vol. 110, No. 1, PP. 55–62.
191
192- Lee, Y., Kim, S.I., Lee, S., Kang, K., (2003). “A location-routing problem in designing optical internet access with WDM systems”, Photonic Network Commu., Vol. 6, No. 2, PP. 151–160.
192
193- Ogryczak, W., Studzinski, K., Zorychta, K., (1989). “A solver for the multi-objective transshipment problem with facility location”, European Journal of Operational Research, Vol. 43, No. 1, PP. 53–64.
193
194- List, G.F., Mirchandani, P.B., (1991). “An integrated network/planar multiobjective model for routing, siting for hazardous materials wastes”, Transportation Science, Vol. 25, No. 2, PP. 146–156.
194
195- ReVelle, C., Cohon, J., Shobrys, D., (1991). “Simultaneous siting, routing in the disposal of hazardous wastes”, Transportation Science, Vol. 25, No. 2, PP. 138–145.
195
196- Ogryczak, W., Studzinski, K., Zorychta, K., (1992). “DINAS: a Computer-assisted analysis system for multiobjective transshipment problems with facility location”, Computer & Operational Research, Vol. 19, No. 7, PP. 637–647.
196
197- Boffey, B., Karkazis, J., (1993). “Models and methods for location and routing decision relating to hazardous materials”, Studies in Locational Analysis, Vol. 5, No. ???, PP. 149–166.
197
198- Stowers. C.L., Palekar. U.S., (1993b). “Location models with routing”, Computer & Operational Research, Vol. 6, No. ???, PP. 427-435.
198
199- Jacobs, T.L., Warmerdam, J.M., (1994). “Simultaneous routing, siting for hazardous-waste”, Operational Journal of Urban Planning, Development, Vol. 120, No. 3, PP. 115–131.
199
200- Current, J., Ratick, S., 1995. “A model to assess risk, equity, efficiency in facility location, Transaction of hazardous materials”, Location Science, Vol. 3, No. 3, PP. 187–201.
200
201- Wyman, M.M., Kuby, M., (1995). “Proactive optimization of toxic waste Transaction, location”, Technology Location Science, Vol. 3, No. 3, PP. 167–185.
201
202- Kulcar, T., (1996). “Optimizing solid waste collection in Brussels”, European Journal of Operational Research, Vol. 90, No. 1, PP. 71–77.
202
203- Giannikos, I., (1998). “A multi objective programming model for locating treatment sites, routing hazardous wastes”, European Journal of Operational Research, 104, No. 2, PP. 333–342.
203
204- Alumur, S., Kara, B. Y. (2007). “A new model for the hazardous waste location routing problem”, Computer & Operational Research, Vol. 34, No. 5, PP. 1406–1423.
204
205- Coutinho-Rodrigues, J., Tralhao, L., Alc¸ ada-Almeida, L., (2012). “Solving a location-routing problem with a multi-objective approach: the design of urban evacuation plans”, Journal of Transportation Geo., Vol. 22, No. ???, PP. 206–218.
205
206- Xie, Y., Lu, W., Wang, W., Quadrifoglio, L., (2012). “A multimodal location, routing model for hazardous materials Transaction”, Journal of Hazardous Mater., Vol. 227, No. ???, PP. 135–141.
206
207- Ehrgott, M., Verma, R., (2001). “A note on solving multi criteria Transportation-location problems by fuzzy programming”, Asia-Pacific Journal of Operational Research, Vol. 18, No. 2, PP. 149–164.
207
208- Boffey, T. et. al. (2008). “Locating a low-level waste disposal site”, Computer & Operational Research, Vol. 35, No. 3, PP. 701–716.
208
209- Martínez-Salazar, I.A., Molina, J., Ángel-Bello, F., Gómez, T., Caballero, R., (2015). “Solving a bi-objective Transportation location routing problem by metaheuristic algorithms”, European Journal of Operational Research, Vol. 234, No. 1, PP. 25–36.
209
210- Gonzalez, F.,J., (2009). “The multi-echelon location-routing problem: Concepts and methods for tactical and operation planning”, Technical Report, Transport Economics Laboratory, Lyon, France.
210
211- Gendron, B., Semet, F. (2009). “Formulations and relaxations for a multi-echelon capacitated location–distribution problem”, Computer and Operational Research, Vol. 36, No. 5, PP. 1335–1355.
211
212- Boccia, M., Crainic, T., Sforza, A., Sterle, C. (2011). “Location-routing models for designing a two-echelon freight distribution system”, Technology Rep., CIRRELT-2011-06, Université de Montréal.
212
213- Contardo, C., Hemmelmayr, V., Crainic, T. G. (2012). “Lower and upper bounds for the two-echelon capacitated location-routing problem”, Computer and Operational Research, Vol. 39, No. 12, PP. 3185–3199.
213
214- Hamidi, M., Farahmand, K., Sajjadi, S.R. (2012). “Modeling a four-layer location-routing problem”, International Journal of Industrial Engineering Computers, Vol. 3, No. ???, PP. 43–52.
214
215- Madsen, O., (1983). “Methods for solving combined two level location-routing problems of realistic dimensions”, European Journal of Operational Research, Vol. 12, No. 3, PP. 295–301.
215
216- Burks, R., (2006). “An adaptive tabu search heuristic for the location routing pickup and delivery problem with time windows with a theater distribution application”, PhD thesis, Graduate School of Engineering and Management, Air Force Institute of Technology, Ohio.
216
217- Lin, J.R., Lei, H.C., (2009). “Distribution systems design with two-level routing considerations”, Annals of Operational Research, Vol. 172, No. 1, PP. 329–347.
217
218- Boccia, M., Crainic, T., Sforza, A., Sterle, C. (2010). “A metaheuristic for a two echelon location-routing problem”, In P. Festa, Symposium on experimental algorithms (SEA 2010). Lecture notes in Computer Science (6049, 288–301). Berlin: Springer-Verlag.
218
219- Nguyen, V.P., Prins, C., Prodhon, C. (2010). “A multi-start evolutionary local search for the two-echelon location routing problem”, in Blesa, et. al., Hybrid Metaheuristics, Vol. 6373 of Lecture Notes in Computer Science, Springer, p. 88–102.
219
220- Nikbakhsh, E., Zegordi, S. (2010). “A heuristic algorithm and a lower bound for the two-echelon location-routing problem with soft time window constraints”, Scientia Iranica Transaction E: Industrial Engineering, Vol. 17, No. ???, PP. 36–47.
220
221- Crainic, T. G., Sforza, A., Sterle, C. (2011a). “Tabu search heuristic for a two-echelon location-routing problem”, Technical Report 2011-07, CIRRELT, Canada.
221
222- Hamidi, M., Farahmand, K., Sajjadi, S.R., Nygard, K. (2012). “A hybrid GRASP tabu search metaheuristic for a four-layer location-routing problem”, International Journal of Logistics System and Management, Vol. 12, No. ???, PP. 267–287.
222
223- Nguyen, V.P., Prins, C., Prodhon, C., (2012a). “A multi-start iterated local search with tabu list, path relinking for the two-echelon location-routing problem”, Engineering Application of Artificial Intell., Vol. 25, No. 1, PP. 56–71.
223
224- Nguyen, V.P., Prins, C., Prodhon, C. (2012b). “Solving the two-echelon location routing problem by a GRASP reinforced by a learning process, path relinking”, European Journal of Operational Research, Vol. 216, No. 1, PP. 113–126.
224
225- Toyoglu, H., Karasan, O.E., Kara, B.Y., (2012). “A new formulation approach for location-routing problems”, Networks, Spatial Economics, Vol. 12, No. 4, PP. 635–659.
225
226- Hamidi, M., Farahmand, K., Sajjadi, S.R., Nygard, K. (2014). “A heuristic algorithm for a multi-product four-layer capacitated location-routing problem”, International Journal of Industrial Engineering Comput., Vol. 5, No. 1, PP. 87–100.
226
227- Rahmani, Y. et. al. (2015). “The two-echelon multi products location-routing problem with pickup and delivery: formulation and heuristic approaches”, International Journal of Production Research, Vol. 54, No. 4, PP. 999-1019.
227
228- Jowkar, A., Sahraeian, R., (2011). “Solving multi-level location-routing problem due to limitations in storage capacity and restrictions on the path using heuristic methods”, MS thesis, University Shahed.
228
229- Crainic, T. G., Sforza, A., Sterle, C. (2011b). “Location-routing models for two-echelon freight distribution system design”, Technical report 2011-40, CIRRELT, Canada. Transportation, Amsterdam: Elsevier, PP. 467–537.
229
230- Hamidi, M., (2011). “Modeling And Solving Multi-Product Multi-Layer Location-routing Problems”, PhD dissertation, University of North Dakota State.
230
231- Schwengerer, M., Pirkwieser, S., Raidl, G.R., (2012). “A variable neighborhood search approach for the two-echelon location-routing problem”, In J. K. Hao & M. Middendorf (Eds.), Evolutionary computation in combinatorial optimization. Lecture notes in Computer Science (Vol. 7245, PP. 13–24). Berlin Heidelberg: Springer.
231
232- Dalfard, V.M., Kaveh, M., Nosratian, N.E., (2013). “Two meta-heuristic algorithms for two echelon location-routing problem with vehicle fleet capacity and maximum route length constraints”, Neural Comput. Appl., Vol. 23, No. ???, PP. 2341–2349.
232
233- Govindan, K., Jafarian, A., Khodaverdi, R., Devika, K. (2014). “Two-echelon multiple vehicle LRP with time windows for optimization of sustainable supply chain network of perishable food”, International Journal of Production Economics, Vol. 152, No. ???, PP. 9–28.
233
234- Zegordy, S.H.A., nikbakhsh, A., (2009). “Solutions lower bound and innovative for the two-level location routing problem”, International Journal of Industrial Engineering & Production Management, Vol. 20, No. 1, PP. 1-14.
234
235- Jiahong, Z., Vedat, V., (2015). “A bi-objective model for the used oil location-routing problem”, Computer and Operational Research, Vol. 62, No. ???, PP. 157–168.
235
236- Jin, L., Zhu, Y., Shen, H., Ku, T. (2010). “Research on two-layer location-routing problem and optimization algorithm”, International Journal of Advancment in Computers Technology, Vol. 2, No. ???, PP. 102–108.
236
237- Barzinpour, F., Saffarian, M., Teymoori, E., (2015a). “Metahuristic algorithm for solving model of multi-objective location programming and three-level allocation in relief logistics”, Journal of Operational Research in Its Application, Vol. 2, No. 41, PP. 27-50.
237
238- Berman, O., Simchi-Levi, D., (1986). “Minisum location of a traveling salesman”, Networks, Vol. 16, No. 3, PP. 239–254.
238
239- Berman, O., Simchi-Levi, D., (1988a). “Minisum location of a travelling salesman on simple networks”, European Journal of Operational Research, Vol. 36, No. 2, PP. 241–250.
239
240- Berman, O., Simchi-Levi, D., (1988b). “Finding the optimal a priori tour, location of a traveling salesman with nonhomogeneous customers”, Transportation Science, Vol. 22, No. 2, PP. 148–154.
240
241- Berman, O., Simchi-Levi, D., Tamir, A., (1988). “The minimax multistop location problem on a tree”, Networks, Vol. 18, No. 1, PP. 39–49.
241
242- Berman, O., Simchi-Levi, D., (1989). “The traveling salesman location problem on stochastic networks”, Transportation Science, Vol. 23, No. 1, PP. 54–57.
242
243- Bertsimas, D.J., (1989). “Traveling salesman facility location problems”, Transportation Science, Vol. 23, No. 3, PP. 184–191.
243
244- Bertsimas, D.J., Jaillet, P., Odoni, A.R., (1990). “A priori optimization”, Operational Research, Vol. 38, No. 6, PP. 1019–1033.
244
245- McDiarmid, C, (1992). “Probability modelling, optimal location of a travelling salesman”, Journal of the Operational Research Society., Vol. 43, No. 5, PP. 533–538.
245
246- Averbakh, I., Berman, O., Simchi-Levi, D., (1994). “Probabilistic a priori routing-location problems”, Naval Research Logistics, Vol. 41, No. 7, PP. 973–989.
246
247- Averbakh, I., Berman, O., (1995). “Probabilistic sales-delivery man, sales-delivery facility location problems on a tree”, S Transportation Science, Vol. 29, No. 2, PP. 184–197.
247
248- Simchi-Levi, D., Berman, O., (1987). “Heuristics and bounds for the travelling salesman location problem on the plane”, Operational Research Letters, Vol. 6, No. 5, PP. 243–248.
248
249- Simchi-Levi, D., Berman, O., (1988). “A heuristic algorithm for the traveling salesman location problem on networks”, European Journal of Operational Research, Vol. 36, No. ???, PP. 478-484.
249
250- Simchi-Levi, D., (1991). “The capacitated traveling salesman location problem”, Transportation Science, Vol. 25, No. 1, PP. 9–18.
250
251- Mosheiov, G., 1995. “The pickup delivery location problem on networks”, Networks, Vol. 26, No. 4, PP. 243–251.
251
252- Laporte, G., Louveaux, F., Mercure, H., (1989). “Models, exact solutions for a class of stochastic location-routing problems”, European Journal of Operational Research, Vol. 39, No. 1, PP. 71–78.
252
253- Chan, Y., Carter, W.B., Burnes, M.D., (2001). “A multiple-depot, multiple-vehicle, location-routing problem with stochastically processed demands”, Computer & Operational Research, Vol. 28, No. 8, PP. 803–826.
253
254- Liu, S., Lin, C., (2005). “A heuristic method for the combined location routing and inventory problem”, International Journal of Advanced Manufacturing Technology, Vol. 26, No. 4, PP. 372–381.
254
255- Albareda-Sambola, M., Fernandez, E., Laporte, G., (2007). “Heuristic, lower bound for a stochastic location-routing problem”, European Journal of Operational Research, Vol. 179, No. 3, PP. 940–955.
255
256- Shen, Z., Qi, L. (2007). “Incorporating inventory and routing costs in strategic location models”, European Journal of Operational Research, Vol. 179, No. 2, PP. 372–389.
256
257- Zarandi, M.H.F., Hemmati, A., Davari, S., Turksen, I.B., (2013). “Capacitated location-routing problem with time windows under uncertainty”, Knowledge-Based System, Vol. 37, No. ???, PP. 480–489.
257
258- Sajjadi, R.S., Cheraghi, H.S. (2011). “Multi-products location-routing problem integrated with inventory under stochastic demand”, International Journal of Industrial and Systems Engineering, Vol. 7, No. 4, PP. 454–476.
258
259- Hassan-Pour, H.A., Mosadegh-Khah, M., Zareei, M., (2014). “An Efficient Algorithm for Solving a Stochastic Location-Routing Problem”, Journal of Mathematics and Computer Science, Vol. 12, PP. 27–38.
259
260- Hassanpour, H., Mosaddegh-khah, M., Tavakkoli-Moghaddam, R., (2007). Developing two mathematical models for stocastice location-routing problem, 5th InternationalIndustrialEngineering Con., Tehran, Iran.
260
261- Hassan-Pour, H., et. al. (2009). “Solving a multi-objective multi-depot stochastic location-routing problem by a hybrid simulated annealing algorithm”, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacturing, Vol. 223, No. 8, PP. 1045-1054.
261
262- Nadizadeh, A., Hosseini Nasab, H. (2014). “Solving the dynamic capacitated location routing problem with fuzzy demands by hybrid heuristic algorithm”, European Journal of Operational Research, Vol. 238, No. ???, PP. 458–470.
262
263- Nadizadeh, A., Hosseini Nasab, H., Sadeghieh, A., Fakhrzad, M.B., (2014). “A location-routing problem model with multiple periods and fuzzy demands”, Journal of Data Envelopment Analysis & Decision Science, PP. 1-24.
263
264- Ghaffari-Nasab, N., Ghazanfar Ahari, S., Ghazanfari, M., (2013), “A hybrid simulated annealing based heuristic for solving the location-routing problem with fuzzy demands”, Scientia Iranica, Vol. 20, No. 3, PP. 919–930.
264
265- Shouying, L., Huijuan, Z., (2014). “Optimization model of fuzzy location-routing problem of victim search in flood disaster”, Journal of Chemical and Pharmaceutical Research, Vol. 6, No. 6, PP. 2080-2085.
265
266- Teimoori, S., Khademi-Zare, H., Fallah-Nezhad, M.S., (2014). “Location-routing problem with fuzzy time windows and traffic time”, International Journal of Supply & Operational Management, Vol. 1, No. 1, PP. 38-53.
266
267- Torfi, F., Farahani, R.Z., Mahdavi, I., (2015). “Fuzzy MCDM for weight of object’s phrase in Location Routing Problem”, Applied Mathematics Modeling, Vol. 40, No. 1, PP. 526–541.
267
268- S., Li, H., Zhou, Y., Li, (2016). “Research on Fuzzy Dynamic Location-Routing Problem of Victim Search in Flood Disaster”, International Journal of u- and e- Service, Science & Technology, Vol. 9, No. 7, PP. 61-70.
268
269- Golozari, F., (2008). “Using simulated annealing algorithm mutation operator combined for location-routing problem fuzzy with limited capacities”, MS thesis, University of Science and Art.
269
270- Teymoori, SH., (2013). “Developed a mathematical model and algorithm for location routing problem with fuzzy time windows”, MS thesis, University of Science and Art.
270
271- Barzinpour, F., Saffarian, M., Maku, A., Teymoori, E., (2015b). “Model of multi-objective Location Routing Problem in the relief chain management with multi period approach”, Journal of Operational Research in Its Application, Vol. 3, No. 42, PP. 71-91.
271
272- Mahdizadeh,E., Keshavarzi, S., (2015). “Multi-objective model for location routing problem with fuzzy time travel and delivery”, Journal of Supply Chain Management, Vol. 17, No. 47, PP. 42-61.
272
273- Chan, A.W., Hearn, D.W., (1977). “A rectilinear distance round-trip location problem”, Transportation Science, Vol. 11, No. 2, PP. 107–123.
273
274- Ghosh, J.K., Sinha, S.B., Acharya, D., (1981). “A generalized reduced gradient based approach to round-trip location problem”, in: Jaiswal, N.K. (Ed.), Scientific Management of Transport Systems, Amsterdam, Holland, 209- 213.
274
275- Drezner, Z., (1982). “Fast algorithms for the round trip location problem”, IEE Transactions, Vol. 14, No. 4, PP. 243–248.
275
276- Drezner, Z., Wesolowsky, G.O., (1982). “A trajectory approach for the round-trip location problem”, Transportation Science, Vol. 16, No. 1, PP. 56–66.
276
277- Drezner, Z., (1985). “O(N log N) algorithm for the rectilinear round-trip location problem”, Transportation Science, Vol. 19, No. 1, PP. 91–100.
277
278- Kolen, A., (1985). “The round-trip p-center, covering problem on a tree”, Transportation Science, Vol. 19, No. 3, PP. 222–234.
278
279- Bruns, A.D., (1998). “Zweistufige Standort planung unter Berucksichtigung von Touren planungsaspekten – Primale Heuristiken und Lokale Suchverfahren”, PhD Dissertation, Sankt Gallen University.
279
280- De Camargo, R., de Miranda, G., Lkketangen, A. (2013). “A new formulation and an exact approach for the many-to-many hub location-routing problem”, Applied Mathematics Modelling, Vol. 37, No. 12, PP. 7465–7480.
280
281- Nagy, G., Salhi, S., (1998). “The many-to-many location-routing problem”, TOP, Vol. 6, No. 2, PP. 261–275.
281
282- Karaoglan, I., Altiparmak, F., Kara, I., Dengiz, B. (2012). “The location-routing problem with simultaneous pickup and delivery: Formulations and a heuristic approach”, Omega, Vol. 40, No. 4, PP. 465–477.
282
283- Rieck, J., Ehrenberg, C., Zimmermann, J. (2014). “Many-to-many location-routing with inter-hub transport and multi-commodity pickup-and-delivery”, European Journal of Operational Research,Vol. 236, No. 3, PP.863–878.
283
284- Ahmadi-Javid, A., Seddighi, A. (2012). “A location-routing-inventory model for designing multisource distribution networks”, Engineering Optimization, Vol. 44, No. 6, PP. 637–656.
284
285- Taei, A., (2011). “The locating - Routing - inventory problem with deteriorating ware”, MS Thesis, K. N. Toosi University of Technology.
285
286- Safari, S., Pasandideh, S.H.R., (2014), “Stocastic models location-routing-inventory supply chain with heterogeneous transport fleet”, National Conference on Research of Industrial Engineering, 27 Sep 2014, Hamedan, Iran.
286
287- Riquelme-Rodríguez, J.P., Gamache, M., Langevin, A. (2016). “Location arc routing problem with inventory constraints”, Computers & Operational Research, Vol. 76, No. 1, PP. 84-94.
287
288- Ahmadi, A., Azad,N., (2010). “Incorporating location, routing, inventory decisions in supply chain network design”, Transportation Research Part E, Vol. 46, No. 5, PP. 582–597.
288
289- Belenguer, J.M., Benavent, E., Lacomme, P., Prins, C. (2006). “Lower and upper bounds for the mixed capacitated arc routing problem”, Computer Operational Research, Vol. 33, No. 12, PP. 3363–3383.
289
290- Ghiani, G., Laporte, G. (2001).“Location-arc routing problems.” Opsearch, Vol. 38, No. 2, 151–159.
290
291- Hashemi Doulabi, S. H., Seifi, A. (2013). “Lower and upper bounds for location-arc routing problems with vehicle capacity constraints”, European Journal of Operational Research, Vol. 224, No. 1, PP. 189–208.
291
292- Lopes, R.B., Plastria, F., Ferreira, C., Santos, B.S. (2014). “Location-arc routing problem: Heuristic approaches and test instances”, Computer & Operational Research, Vol. 43, No. 1, PP. 309–317.
292
293- Salhi, S., Nagy, G., (2009). “Local improvement in planar facility location using vehicle routing”, Annals of Operational Research, Vol. 167, No. 1, PP. 287–296.
293
294- Schwardt, M., Fischer, K., (2009). “Combined location-routing problems – a neural network approach”, Annals of Operational Research, Vol. 167, No. 1, PP. 253–269.
294
295- Manzour-al-Ajdad, S., Torabi, S., Salhi, S. (2012). “A hierarchical algorithm for the planar single-facility location routing problem”, Computer and Operational Research, Vol. 39, No. 2, PP. 461–470.
295
296- Beasley, J.E., Nascimento, E.M., (1996). “The vehicle routing-allocation problem: A unifying framework”, TOP., Vol. 4, No. 1, PP. 65–86.
296
297- Labbe, M., Laporte, G., Martin, I.R., Salazar Gonzalez, J.J., (2005). “Locating median cycles in networks”, European Journal of Operational Research, Vol. 160, No. 2, PP. 457–470.
297
298- Gunnarsson, H., Ronnqvist, M., Carlsson, D., (2006). “A combined terminal location, ship routing problem”, Journal of the Operational Research Society, Vol. 57, No. 8, PP. 928–938.
298
299- Sadeghi, A., (2011), “Solving split delivery open location routing problem using simulated annealing algorithm”, MS Thesis, University of Science & Culture.
299
300- Jafari, A., Sadeghi Sarvestani, A., (2014). “Modeling the split delivery open location routing problem and solving it by simulated annealing”, Journal of Industrial Engineering Research in Production System, Vol. 2. No. 3. PP. 47-61.
300
301- Labbe, M., Rodriguez Martin, I. and Salazar Gonzalez, J. J. (2004). “A branch-and-cut algorithm for the plant-cycle location problem”, Journal of the Operational Research Society, Vol. 55, No. 5, PP. 513–520.
301
302- Billionnet, A., Elloumi, S. and Grouz-Djerbi, L. (2005). “Designing radio-mobile access networks based on synchronous digital hierarchy rings”, Computer & Operational Research, Vol. 32, No. 2, PP. 379–394.
302
303- Laporte, G. AND Dejax, P. J. (1989). “Dynamic location-routeing problems”, Journal of the Operational Research Society, Vol. 40, No. 5, PP. 471–482.
303
ORIGINAL_ARTICLE
Minimizing Net Present Value of Costs in Lot-Sizing in a Two-Echelon Inventory System
In this paper, a two-echelon supplier-manufacturer system has been studied through net present value (NPV) approach. The production rate is finite and constant in both echelons. Also it is assumed that there is a lead-time between the first echelon and it is getting to the second echelon. It is also assumed that the lot-size of manufacturer (second echelon) is m times larger than the supplier’s factors (first echelon), and the supplier can receive wares (the raw material) from the manufacturer in a cycle through several shipments, due to the point that shortage is not allowed. So, it is supposed that the supplier’s production rate is greater than manufacturer’s. The aim is to determine the optimal lot-size of each echelon such that the NPV of the total cost of system is minimized. After approximating the NPV objective function via Maclaurin expansion in both zero and non-zero lead-time cases, an exact algorithm is presented to find optimal solution of the presented model. Based on the results, the two approaches of average cost and NPV do not lead to a same result, and non-equivalency is occurred in this case.
https://aie.ut.ac.ir/article_62215_c56b55a1c4c3e8bdba30d2cc8dc1b5d3.pdf
2017-06-22
251
264
10.22059/jieng.2017.62215
Economic production quantity
Lead-time
Time values of money
Two-Echelon inventory system
Yaser
Malekiyan
malekiyan@gmail.com
1
Department of Industrial and Systems Engineering, Isfahan University of Technology, Isfahan, Iran
AUTHOR
Seyed Hamid
Mirmohammadi
h_mirmohammadi@cc.iut.ac.ir
2
Department of Industrial and Systems Engineering, Isfahan University of Technology, Isfahan, Iran
LEAD_AUTHOR
Muller, H. E. (2009). “Supplier integration: an international comparison of supplier and automaker experiences”, International Journal of Automotive Technology and Management, Vol. 9, No.1, PP. 18-39.
1
Clark, A. J. (1958). “A dynamic, single-item, multi-echelon inventory model”, RM-2297, Rand Corporation, Santa monica, California
2
Clark, A. J. and Scarf, H. (1960). “Optimal policies for a multi-echelon inventory problem”, Management Science, Vol. 6, No. 4, PP. 475–490.
3
Goyal, S. (1976). “An integrated inventory model for a single supplier-single customer problem”, International Journal of Production Research, Vol. 15, No. 1, PP. 107–111.
4
Banerjee, A. (1986). “A joint economic-lot-size model for purchaser and vendor”, Decision Sciences, Vol. 17, No. 3, PP. 292–311.
5
Goyal, S. (1988). “A joint economic‐lot‐size model for purchaser and vendor”, Management Science, Vol. 19, No. 1, PP. 236–241.
6
Monahan, J. (1984). “A quantity discount pricing model to increase vendor profits”, Management Science, Vol. 30, No. 6, PP. 720–726.
7
Lee, H. L. and Rosenblatt, M. J. (1986). “A generalized quantity discount pricing model to increase supplier's profits”, Management Science, Vol. 32, No. 9, PP. 1177–1185.
8
Hwang, H. and Kim, K.H. (1986). “Supplier's discount policy with a single price break point”, Production Economics Supply, Vol. 10, No. 1, PP. 279–286.
9
Kim, K. H. and Hwang, H. (1989). “Simultaneous improvement of supplier's profit and buyer's cost by utilizing quantity discount”, J Oper Res Soc, Vol. 40, No. 3, PP. 255–265.
10
Joglekar, P. N. (1988). Note—Comments on “A quantity discount pricing model to increase vendor profits”, Management Science, Vol. 34, No. 11, PP. 1391–1398.
11
Beullens, P. and Janssens, G. K. (2014). “Adapting inventory models for handling various payment structures using net present value equivalence analysis”, International Journal of Production Economics, Vol. 157, No. 1, PP. 190–200.
12
Silver, E. A., Peterson, R. and Pyke, D. F. (1998). Inventory Management and Production Planning and Scheduling, Wiley, New York.
13
Hillier, F. S. and Lieberman, G. J. (2005). Introduction to operations research, McGraw-Hill, New York, London.
14
Beullens, P. (2014). “Revisiting foundations in lot sizing-connections between Harris, Crowther, Monahan, and Clark”, International Journal of Production Economics, Vol. 155, No. 1, PP. 68–81.
15
Lu, L. (1995). “A one-vendor multi-buyer integrated inventory model”, European Journal of Operational Research, Vol. 81, No. 2, PP. 312–323.
16
Goyal, S. K. (1995). “A one-vendor multi-buyer integrated inventory model: A comment”, European Journal of Operational Research, Vol. 82, No. 1, PP. 209–210.
17
Hill, R. M. (1999). “The optimal production and shipment policy for the single-vendor single buyer integrated production-inventory problem”, International Journal of Production Research, Vol. 37, No. 11, PP. 2463–2475.
18
Hill, R. and Omar, M. (2006). “Another look at the single-vendor single-buyer integrated production-inventory problem”, International Journal of Production Research, Vol. 44, No. 4, PP. 791–800.
19
Munson, C. and Rosenblatt, M. (2001). “Coordinating a three-level supply chain with quantity discounts”, IIE Transactions, 33, No. 5, 371–384.
20
Van der Laan, E., and Teunter, R. (2002). “Average costs versus net present value: a comparison for multi-source inventory models”, Quantitative Approaches to Distribution Logistics and Supply Chain Management, PP. 359–378, Springer, Berlin Heidelberg
21
Beullens, P. and Janssens, G. K. (2011). “Holding costs under push or pull conditions – the impact of the anchor point”, European Journal of Operational Research, Vol. 215, No. 1, PP. 115–125.
22
Ben-Daya, M. and Al-Nassar, A. (2008). “An integrated inventory production system in a three-layer supply chain”, Production Planning and Control, Vol. 19, No. 2, PP. 97–104.
23
Giri, B. and Bardhan, S. (2011). “Coordinating a two-echelon supply chain under inflation and time value of money”, International Journal of Industrial Engineering Computations, Vol. 2, No. 4, PP. 811–818.
24
Gloc, C., and Kim., T. (2014). “Shipment consolidation in a multiple-vendor single-byer integrated inventory model”, Computers and Industrial Engineering, Vol. 70, No. 1, PP. 31–24.
25
Sadjadi, S., Zokaee, S. and Dabiri, N. (2014). “A single-vendor single-buyer joint economic lot size model subject to budget constraints”, The International Journal of Advanced Manufacturing Technology, Vol. 70, No. 9-12, PP. 1699–1707.
26
Malekian, Y. and Mirmohammadi S. H. (2015). “Determination of joint economic lot-size in a two-echelon production system with finite rate considering lead-time”, International Journal of Optimization in Civil Engineering, Vol. 5, No. 3, PP. 375–389.
27
Glock, C. H. (2012). “The joint economic lot size problem: a review”, International Journal of Production Economics, Vol. 135, No. 2, PP. 671–686.
28
Grubbström, R. W. (1967). “On The Application of the laplace transform to certain economic problems”, Management Science, Vol. 13, No. 7, PP. 558–567.
29