A mathematical model of the location problem for central and secondary warehouses in the multi-level supply chain network of perishable products

Mousavi, Seyyed Mostafa; Motamedi, Majid; Karimi, Rasoul

doi:10.22105/riej.2024.394527.1378

Document Type : Research Paper

Authors

¹ Department of Technical and Engineering, Nowshahr Branch, Islamic Azad University, Nowshahr, Iran.

² Department of Industrial Management, Nowshahr Branch, Islamic Azad University, Nowshahr, Iran.

https://doi.org/10.22105/riej.2024.394527.1378

Abstract

A supply chain is a network that creates and delivers products and services to customers. In this research, the four-level supply chain in the field of food products, including the levels of supplier, customer, and central and secondary warehouses, has been investigated. A mixed integer mathematical model of the research problem is presented to minimize chain costs, including the setting up and preparation of warehouses, transportation between transfer levels, and holding products. The proposed model is developed based on constraints such as inventory, warehouse capacity, vehicle capacity, and multi-period multi-product. The decision variables are determined after solving the model, which includes the optimal number of central and secondary warehouses, the optimal amount of product transferred between the factory and central warehouse, the central warehouse and secondary warehouse, and the secondary warehouse and customer, the optimal amount of product storage in secondary warehouses, the type of vehicle for transportation between levels, and the capacity level of each product in each central warehouse. To validate the proposed model, experiments were conducted using the Kaleh company's real data in GAMS software. Finally, the sensitivity analysis of the model was carried out on two critical parameters influencing decision-making: demand and the cost of increasing the capacity of the central warehouse. The output results confirmed the validity and efficiency of the proposed model.

Keywords

Main Subjects

Mathematical modelling

References

[1] Mayer, G., & Wagner, B. (2002). HubLocator: an exact solution method for the multiple allocation hub location problem. Computers & operations research, 29(6), 715–739. DOI:10.1016/S0305-0548(01)00080-6

[2] Marianov, V., & Serra, D. (2003). Location models for airline hubs behaving as M/D/c queues. Computers & operations research, 30(7), 983–1003. DOI:10.1016/S0305-0548(02)00052-7

[3] Martı́n, J. C., & Román, C. (2004). Analyzing competition for hub location in intercontinental aviation markets. Transportation research part E: logistics and transportation review, 40(2), 135–150. DOI:10.1016/S1366-5545(03)00037-1

[4] Topcuoglu, H., Corut, F., Ermis, M., & Yilmaz, G. (2005). Solving the uncapacitated hub location problem using genetic algorithms. Computers & operations research, 32(4), 967–984. DOI:10.1016/j.cor.2003.09.008

[5] Yaman, H., Kara, B. Y., & Tansel, B. Ç. (2007). The latest arrival hub location problem for cargo delivery systems with stopovers. Transportation research part B: methodological, 41(8), 906–919. DOI:10.1016/j.trb.2007.03.003

[6] Azadeh, A., Ghaderi, S. F., & Maghsoudi, A. (2008). Location optimization of solar plants by an integrated hierarchical DEA PCA approach. Energy policy, 36(10), 3993–4004. DOI:10.1016/j.enpol.2008.05.034

[7] Contreras, I., Fernández, E., & Marín, A. (2010). The tree of hubs location problem. European journal of operational research, 202(2), 390–400. DOI:10.1016/j.ejor.2009.05.044

[8] Sender, J., & Clausen, U. (2011). A new hub location model for network design of wagonload traffic. Procedia - social and behavioral sciences, 20, 90–99. DOI:10.1016/j.sbspro.2011.08.014

[9] Gelareh, S., & Nickel, S. (2011). Hub location problems in transportation networks. Transportation research part e: logistics and transportation review, 47(6), 1092–1111. DOI:10.1016/j.tre.2011.04.009

[10] Alumur, S. A., Nickel, S., & Saldanha-da-Gama, F. (2012). Hub location under uncertainty. Transportation research part B: methodological, 46(4), 529–543. DOI:10.1016/j.trb.2011.11.006

[11] Aros-Vera, F., Marianov, V., & Mitchell, J. E. (2013). P-hub approach for the optimal park-and-ride facility location problem. European journal of operational research, 226(2), 277–285. DOI:10.1016/j.ejor.2012.11.006

[12] Chang, K. L., Liao, S. K., Tseng, T. W., & Liao, C. Y. (2015). An ANP based TOPSIS approach for Taiwanese service apartment location selection. Asia pacific management review, 20(2), 49–55. DOI:10.1016/j.apmrv.2014.12.007

[13] Darestani, S. A., & Hemmati, M. (2019). Robust optimization of a bi-objective closed-loop supply chain network for perishable goods considering queue system. Computers & industrial engineering, 136, 277–292. DOI:10.1016/j.cie.2019.07.018

[14] Aazami, A., & Saidi-Mehrabad, M. (2021). A production and distribution planning of perishable products with a fixed lifetime under vertical competition in the seller-buyer systems: A real-world application. Journal of manufacturing systems, 58, 223–247. DOI:10.1016/j.jmsy.2020.12.001

[15] Tavana, M., Tohidi, H., Alimohammadi, M., & Lesansalmasi, R. (2021). A location-inventory-routing model for green supply chains with low-carbon emissions under uncertainty. Environmental science and pollution research, 28(36), 50636–50648. DOI:10.1007/s11356-021-13815-8

[16] Shavarani, S. M., Golabi, M., & Izbirak, G. (2021). A capacitated biobjective location problem with uniformly distributed demands in the UAV‐supported delivery operation. International transactions in operational research, 28(6), 3220–3243. DOI:10.1111/itor.12735

[17] Liu, Y., Yuan, Y., Shen, J., & Gao, W. (2021). Emergency response facility location in transportation networks: A literature review. Journal of traffic and transportation engineering, 8(2), 153–169. DOI:10.1016/j.jtte.2021.03.001

[18] Ghasemi, P., & Khalili-Damghani, K. (2021). A robust simulation-optimization approach for pre-disaster multi-period location–allocation–inventory planning. Mathematics and computers in simulation, 179, 69–95. DOI:10.1016/j.matcom.2020.07.022

[19] Liu, A., Zhu, Q., Xu, L., Lu, Q., & Fan, Y. (2021). Sustainable supply chain management for perishable products in emerging markets: An integrated location-inventory-routing model. Transportation research part e: logistics and transportation review, 150, 102319. DOI:10.1016/j.tre.2021.102319

[20] Azami, A. ., Saidi-Mehrabad, M. ., & Seyedhosseini, S. . (2021). A bi-objective robust optimization model for an integrated production-distribution problem of perishable goods with demand improvement strategies: a case study. International journal of engineering, 34(7), 1766-1777. DOI:10.5829/ije.2021.34.07a.21

[21] Acevedo-Chedid, J., Soto, M. C., Ospina-Mateus, H., Salas-Navarro, K., & Sana, S. S. (2023). An optimization model for routing—location of vehicles with time windows and cross-docking structures in a sustainable supply chain of perishable foods. Operations management research, 16(4), 1742–1765. DOI:10.1007/s12063-023-00379-8

International Journal of Research in Industrial Engineering

A mathematical model of the location problem for central and secondary warehouses in the multi-level supply chain network of perishable products

References

References

Volume 13, Issue 1
March 2024
Pages 11-24

A mathematical model of the location problem for central and secondary warehouses in the multi-level supply chain network of perishable products

References

References

Volume 13, Issue 1March 2024Pages 11-24

Volume 13, Issue 1
March 2024
Pages 11-24