The Inventory–Routing Problem for Distribution of Red Blood Cells considering Compatibility of Blood Group and Transshipment between Hospitals

Document Type : Research Paper

Authors

1 Institute for Management and Planning Studies (IMPS), Tehran, Iran

2 School of Industrial Engineering, Iran University of Science & Technology

Abstract

This paper presents an inventory-routing problem (IRP) for Red Blood Cells (RBCs) distribution, in which -to avoid shortage- supplying the demand with compatible blood groups (substitution) and the RBC transshipments between hospitals (transshipment) are considered. The mentioned problem is investigated in four conditions: 1- Allowing the transshipment and substitution, 2- Allowing the transshipment, but no substitution, 3- Allowing the substitution, but no transshipment, 4- No allowing the transshipment and substitution. Since the mentioned problem is NP-Hard, the adaptive large neighborhood search algorithm (ALNS) has been used to solve all conditions. The cost in the first condition is the least one, because the feasible solution space is the largest. Also, the results show that the transshipment has a more active role than the substitution in reducing the shortage. Moreover, in the first and third conditions, the O+ blood group is used more than the other blood groups to meet the other compatible blood groups' demands.

Keywords


[1] Hosseini-Motlagh, S. M., Larimi, N. G., & Nejad, M. O. (2020). A qualitative, patient-centered perspective toward plasma products supply chain network design with risk controlling. Operational Research, 1-46. DOI 10.1007/s12351-020-00568-4
[2] Osorio, A. F., Brailsford, S. C., and Smith, H. K. (2015). “A structured review of quantitative models in the blood supply chain: a taxonomic framework for decision-making”. International Journal of Production Research, Vol. 53, No. 24, PP. 7191-7212.
[3] Gunpinar, S., and Centeno, G. (2015). “Stochastic integer programming models for reducing wastages and shortages of blood products at hospitals”. Computers & Operations Research, Vol. 54, PP. 129-141.
[4] Federgruen, A., Prastacos, G., and Zipkin, P. H. (1986). “An allocation and distribution model for perishable products”. Operations Research, Vol. 34, No. 1, PP. 75-82.
[5] Hemmelmayr, V., Doerner, K. F., Hartl, R. F., and Savelsbergh, M. W. (2009). “Delivery strategies for blood products supplies”. OR spectrum, Vol. 31, No. 4, PP. 707-725.
[6] Hemmelmayr, V., Doerner, K. F., Hartl, R. F., and Savelsbergh, M. W. (2010). “Vendor managed inventory for environments with stochastic product usage”. European Journal of Operational Research, Vol. 202, No. 3, PP. 686-695.
[7] Jafarkhan, F., & Yaghoubi, S. (2018). An efficient solution method for the flexible and robust inventory-routing of red blood cells. Computers & Industrial Engineering, 117, 191-206.
[8] Jafarkhan, F., & Yaghoubi, S. (2017). A robust mathematical model and heuristic solution algorithm for integrated production-routing-inventory problem of perishable products with lateral transshipment. Journal of Industrial Engineering Research in Production Systems, Vol. 4, PP. 195-211.
[9] Yaghoubi, S., Hosseini-Motlagh, S. M., Cheraghi, S., & Gilani Larimi, N. (2020). Designing a robust demand-differentiated platelet supply chain network under disruption and uncertainty. Journal of Ambient Intelligence and Humanized Computing, Vol. 11, PP. 3231-3258.
[10] Mobasher, A., Ekici, A., and Özener, O. Ö. (2015). “Coordinating collection and appointment scheduling operations at the blood donation sites”. Computers & Industrial Engineering, Vol. 87, PP. 260-266.
[11] Gilani Larimi, N., & Yaghoubi, S. (2019). A robust mathematical model for platelet supply chain considering social announcements and blood extraction technologies. Computers and Industrial Engineering, 137(June), 106014.
[12] Şahinyazan, F. G., Kara, B. Y., and Taner, M. R. (2015). “Selective vehicle routing for a mobile blood donation system”. European Journal of Operational Research, Vol. 245, No. 1, PP. 22-34.
[13] Duan, Q., and Liao, T. W. (2013). “A new age-based replenishment policy for supply chain inventory optimization of highly perishable products”. International Journal of Production Economics, Vol. 145, No. 2, PP. 658-671.
[14] Cumming, P. D., Kendall, K. E., Pegels, C. C., and Seagle, J. P. (1977). “Cost effectiveness of use of frozen blood to alleviate blood shortages”. Transfusion, Vol. 17, No. 6, PP. 602-606.
[15] Sapountzis, C. (1984). “Allocating blood to hospitals from a central blood bank”. European Journal of Operational Research, Vol. 16, No. 2, PP. 157-162.
[16] Sivakumar, P., Ganesh, K., and Parthiban, P. (2008). “Multi-phase composite analytical model for integrated allocation-routing problem-application of blood bank logistics”. International Journal of Logistics Economics and Globalisation, Vol. 1, No. 3-4, PP. 251-281.
[17] Arvan, M., Tavakkoli-Moghaddam, R., and Abdollahi, M. (2015). “Designing a bi-objective and multi-product supply chain network for the supply of blood”. Uncertain Supply Chain Management, Vol. 3, No. 1, PP. 57-68.
[18] Gilani Larimi, N., Yaghoubi, S., & Hosseini-Motlagh, S. M. (2019). Itemized platelet supply chain with lateral transshipment under uncertainty evaluating inappropriate output in laboratories. Socio-Economic Planning Sciences, 68(February 2018), 100697.
[19] Coelho, L. C., Cordeau, J. F., and Laporte, G. (2012). “The inventory-routing problem with transshipment”. Computers & Operations Research, Vol. 39, No. 11, PP. 2537-2548.
[20] Desrochers, M., and Laporte, G. (1991). “Improvements and extensions to the Miller-Tucker-Zemlin subtour elimination constraints”. Operations Research Letters, Vol. 10, No. 1, PP. 27-36.
[21] Archetti, C., Bertazzi, L., Laporte, G., and Speranza, M. G. (2007). “A branch-and-cut algorithm for a vendor-managed inventory-routing problem”. Transportation Science, Vol. 41, No. 3, PP. 382-391.