Providing a New Mathematical Model for School Service Routing with Considering Gender Separation

Document Type: Research Paper

Authors

1 Department of Industrial Engineering, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran

2 Department of Industrial Engineering, Faculty of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

Abstract

In our country, school bus routes are determined by experiments of driver without considering the scientific optimum route and location. Traversing additional routes will always result an increase in vehicle movements and fuel consumption and enormous costs. Hence, this paper will study the school bus routing in Tehran considering special students and a model will be presented to minimize traveling distance and to prevent repetitive crossings through the bus stops and to determine the shortest routes by presenting a way to propel several students to a bus stop. The proposed model will solve via GAMS software. Because the model is NP-Hard, the Genetic algorithm is used to solve the large scale problem. The contribution of this paper is to consider gender separation in schools and buses. To solve this problem, an integer linear programming model is developed. The conclusion indicates a decrease in transportation time.

Keywords

Main Subjects

References

  1. Houda, D., Bassem, J., Saïd, H. and Habib, C. (2012). “Genetic algorithm with iterated local search for solving a location-routing problem”, Journal of Expert Systems with Applications, Vol. 39, No. 3, PP. 2865– 2871.
  2.  Norouzi, N., Tavakkoli-Moghaddam, R., Ghazanfari, M., Alinaghian, M. and Salamatbakhsh, A. (2012). “A new multiobjective competitive open vehicle routing problem solved by particle swarm optimization”, Networks and Spatial Economics, Vol. 14, No.4, PP. 603– 633.
  3.  Fügenschuh, A. (2009). “Solving a school bus scheduling problem with integer programming”, European Journal of Operational Research, Vol. 193, No. 3, PP. 867- 884.
  4. Newton, R. M. and Thomas, W. H. (1969). “Design of school bus routes by computer”, Socio-Economic Planning Sciences, Vol. 3, No. 1, PP. 75- 85.
  5. Banos, R., Ortega, J., Gil, C., Marquez, A. L. and Toro, F. D. (2013). “A hybrid meta-heuristic for multi-objective vehicle routing problems with time windows”, Comput. Ind. Eng, Vol. 65, No.2, PP. 286- 296.
  6. Nahum, O. E., Hadas, Y. and Spiegel, U. (2014). “Multi-objective vehicle routing problems with time windows: A vector evaluated artificial bee colony approach”, Int. J. Comput. Inf. Technol, Vol. 3, No. 1, PP. 41- 47.
  7. Park, J., Tae, H., Kim. and B. I. (2012). “A post-improvement procedure for the mixed load school bus routing problem”, European Journal of Operational Research, Vol. 217, No.1, PP. 204- 213.
  8. Park, J., and Kim, B. I. (2010). “The school bus routing problem: A review”, European Journal of Operational Research, Vol. 202, No.2, PP. 311- 319.
  9. Naseri, A. and Mansouri, E. (2012). “Two-stage algorithm for the taxi in dynamic mode”, Journal of Transportation, Vol. 9, No. 2, PP. 137- 152.
  10. Santos, D, Xavier, E. (2015). “Taxi and ride sharing: A dynamic dial-a-ride problem with money as an incentive”, Expert Systems with Applications, Vol. 42, No. 19, PP. 6728– 6737.
  11.  Liu, M., Luo, Z. and Lim, A. (2015). “A branch-and-cut algorithm for a realistic dial-a-ride problem”, Transportation Research Part B: Methodological, Vol. 81, No. 1, PP. 267– 288.
  12. Molenbruch, Y., Braekers, K., Caris, A. and Berghe, G. (2017). “Multi-directional local search for a bi-objective dial-a-ride problem in patient transportation”, Computers & Operations Research,Vol. 77, No. 1, PP. 58– 71.
  13. Chen, X., Kong, Y., Dang, L., Yane, H. and Xinyue, Y. (2015). “Exact and metaheuristic approaches for a bi-objective school bus scheduling problem”, Vol. 11, No. 4, PP. 1-2.
  14. Kang, M., Kim, S., Felan, T., Choi, H. and Cho, M. (2015). “Development of a genetic algorithm for the school bus routing problem”, International Journal of Software Engineering and Its Applications, Vol. 9, No. 5, PP. 107- 126
  15. William, A., Ellegood, F. and Campbell, J. (2015). “Continuous approximation models for mixed load school bus routing”, Transportation Research Part B, Vol. 77, No. 3, PP. 182– 198.
  16. Lima, F., Pereira, D., Samuel, C. and Nilson, N. (2016). “A mixed load capacitated rural school bus routing problem with heterogeneous fleet: Algorithms for the Brazilian context”, Expert Systems with Applications,Vol. 56, No. 2, PP. 320– 334.
Advances in Industrial Engineering

Volume 50, Issue 2
Autumn 2016
Pages 247-259

Files

Share

How to cite

Statistics