Locating Routing Problem (LRP) of distribution of priority support items to ground forces in war conditions

Document Type : Original Article

Authors

1 Ph.D in industrial engineering, Department of Science and Technology Studies, AJA Command and Staff University, Tehran, Iran. Email: m.abolghasemian.bt@gmail.com

2 Assist. Prof. Department of Science and Technology Studies, AJA Command and Staff University, Tehran, Iran. Email: hamidbigdeli92@gmail.com

3 Assist. Prof. Department of Science and Technology Studies, AJA Command and Staff University, Tehran, Iran. Email: nader.shamami@gmail.com

Abstract

In this research, a mathematical modeling approach is presented to determine efficient locations for deploying support forces using Data Envelopment Analysis (DEA). Additionally, a mixed-integer linear programming model is proposed for routing prioritized support items. The proposed model allows for the adjustment of manageable inputs to improve outputs according to the principle of managerial accessibility, while also maintaining the current levels of unmanageable inputs if they cannot be reduced based on the principle of natural accessibility. Subsequently, routing for the distribution of these prioritized support items is provided using a mixed-integer linear programming model. The proposed model has been used to evaluate 25 potential locations prepared to provide ground support services to assist friendly forces in contested areas, with the aim of ending the conflict in favor of friendly forces. Sixteen viable support locations have been identified. Finally, routing for the distribution of support items to these 16 locations has been presented.

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Main Subjects


Abolghasemian, M., Bigdeli, H., & Shamami, N. (2024). Modeling the positioning of support forces in future battles using data envelopment analysis and the principles of natural and managerial accessibility. Defensive Future Studies, 9(32), 65-98. https://doi.org/10.22034/dfsr.2024.2007554.1720
Arana-Jiménez, M., Sánchez-Gil, M. C., Younesi, A., & Lozano, S. (2021). Integer interval DEA: An axiomatic derivation of the technology and an additive, slacks-based model. Fuzzy sets and systems, 422, 83-105. https://doi.org/10.1016/j.fss.2020.12.011
Asadi, F., Kordrostami, S., Amirteimoori, A., & Bazrafshan, M. (2023). Inverse data envelopment analysis without convexity: double frontiers. Decisions in Economics and Finance, 46(1), 335-354. https://doi.org/10.1007/s10203-022-00377-8
Bigdeli, H., & Mousazadeh, M. (2023). Analytical Hierarchy Process in modeling and solving matrix games in neutrosophic environment and its application in military problems. Military Science and Tactics, 19(64), 5-33. https://doi.org/10.22034/qjmst.2023.544038.1627
Cao, J. X., Wang, X., & Gao, J. (2021). A two-echelon location-routing problem for biomass logistics systems. Biosystems engineering, 202, 106-118. https://doi.org/10.1016/j.biosystemseng.2020.12.007
Cheng, C., Zhu, R., Costa, A. M., Thompson, R. G., & Huang, X. (2021). Multi-period two-echelon location routing problem for disaster waste clean-up. Transportmetrica A: Transport Science, 1-31. https://doi.org/10.1080/23249935.2021.1916644
Du, J., Wang, X., Wu, X., Zhou, F., & Zhou, L. (2022). Multi-objective optimization for two-echelon joint delivery location routing problem considering carbon emission under online shopping. Transportation Letters, 1-19. https://doi.org/10.1080/19427867.2022.2112857
Fakhr Mousavi, S. M., Amirteimoori, A., Kordrostami, S., & Vaez-Ghasemi, M. (2023). Non-radial two-stage network DEA model to estimate returns to scale. Journal of Modelling in Management, 18(1), 36-60. https://doi.org/10.1108/JM2-09-2020-0228
Fallahtafti, A., Ardjmand, E., Young Ii, W. A., & Weckman, G. R. (2021). A multi-objective two-echelon location-routing problem for cash logistics: A metaheuristic approach. Applied Soft Computing, 111, 107685. https://doi.org/10.1016/j.asoc.2021.107685
Gandra, V. M. S., Çalık, H., Wauters, T., Toffolo, T. A., Carvalho, M. A. M., & Berghe, G. V. (2021). The impact of loading restrictions on the two-echelon location routing problem. Computers & Industrial Engineering, 160, 107609. https://doi.org/10.1016/j.cie.2021.107609
Hasanpour Jesri, Z. S., Eshghi, K., Rafiee, M., & Van Woensel, T. (2022). The Multi-Depot Traveling Purchaser Problem with Shared Resources. Sustainability, 14(16), 10190. https://doi.org/10.3390/su141610190
He, D., Ceder, A. A., Zhang, W., Guan, W., & Qi, G. (2023). Optimization of a rural bus service integrated with e-commerce deliveries guided by a new sustainable policy in China. Transportation Research Part E: Logistics and Transportation Review, 172, 103069. https://doi.org/10.1016/j.tre.2023.103069
Heidari, A., Imani, D. M., Khalilzadeh, M., & Sarbazvatan, M. (2022). Green two-echelon closed and open location-routing problem: application of NSGA-II and MOGWO metaheuristic approaches. Environment, Development and Sustainability, 1-37. https://doi.org/10.1007/s10668-022-02429-w  
Huang, N., Li, J., Zhu, W., & Qin, H. (2021). The multi-trip vehicle routing problem with time windows and unloading queue at depot. Transportation Research Part E: Logistics and Transportation Review, 152, 102370. https://doi.org/10.1016/j.tre.2021.102370
Jiao, L., Peng, Z., Xi, L., Guo, M., Ding, S., & Wei, Y. (2022). A multi-stage heuristic algorithm based on task grouping for vehicle routing problem with energy constraint in disasters. Expert Systems with Applications, 118740. https://doi.org/10.1016/j.eswa.2022.118740
Kordrostami, S., Amirteimoori, A., & Noveiri, M. J. S. (2019). Inputs and outputs classification in integer-valued data envelopment analysis. Measurement, 139, 317-325. https://doi.org/10.1016/j.measurement.2019.02.087
Mohamed, I. B., Klibi, W., Sadykov, R., Şen, H., & Vanderbeck, F. (2022). The two-echelon stochastic multi-period capacitated location-routing problem. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2022.07.022
Nedjati, A., Izbirak, G., & Arkat, J. (2017). Bi-objective covering tour location routing problem with replenishment at intermediate depots: Formulation and meta-heuristics. Computers & Industrial Engineering, 110, 191-206. https://doi.org/10.1016/j.cie.2017.06.004
Neira, D. A., Aguayo, M. M., De la Fuente, R., & Klapp, M. A. (2020). New compact integer programming formulations for the multi-trip vehicle routing problem with time windows. Computers & Industrial Engineering, 144, 106399. https://doi.org/10.1016/j.cie.2020.106399
Nozari, H., Tavakkoli-Moghaddam, R., & Gharemani-Nahr, J. (2022). A neutrosophic fuzzy programming method to solve a multi-depot vehicle routing model under uncertainty during the covid-19 pandemic. International Journal of Engineering, 35(2), 360-371. https://doi.org/10.5829/ije.2022.35.02b.12
Pirabán-Ramírez, A., Guerrero-Rueda, W. J., & Labadie, N. (2022). The multi-trip vehicle routing problem with increasing profits for the blood transportation: An iterated local search metaheuristic. Computers & Industrial Engineering, 170, 108294. https://doi.org/10.1016/j.cie.2022.108294
Pourghader Chobar, A., Bigdeli, H., & Shamami, N. (2024). A Mathematical Model of Hub Location for War Equipment under Uncertainty Using Meta-Heuristic Algorithms. Journal of Industrial Engineering and Management Studies, 11(1), 62-83. https://doi.org/10.22116/jiems.2024.449057.1554
Pourmohammadreza, N., & Jokar, M. R. A. (2023). A Novel Two-Phase Approach for Optimization of the Last-Mile Delivery Problem with Service Options. Sustainability, 15(10), 8098. https://doi.org/10.3390/su15108098
Rezaei Kallaj, M., Abolghasemian, M., Moradi Pirbalouti, S., Sabk Ara, M., & Pourghader Chobar, A. (2021). Vehicle routing problem in relief supply under a crisis condition considering blood types. Mathematical Problems in Engineering, 2021. https://doi.org/10.1155/2021/7217182
Shamami, N., Mehdizadeh, E., Yazdani, M., & Etebari, F. (2022). Proposing a Stackelberg mathematical model for weapon-target assignment considering both air and ground attacks. Military Science and Tactics, 18(59), 245-270. https://doi.org/10.22034/qjmst.2022.543952.1628
Wang, Y., Sun, Y., Guan, X., Fan, J., Xu, M., & Wang, H. (2021). Two-echelon multi-period location routing problem with shared transportation resource. Knowledge-Based Systems, 226, 107168. https://doi.org/10.1016/j.knosys.2021.107168
Wang, Y., Zhe, J., Wang, X., Sun, Y., & Wang, H. (2022). Collaborative Multidepot Vehicle Routing Problem with Dynamic Customer Demands and Time Windows. Sustainability, 14(11), 6709. https://doi.org/10.3390/su14116709
Xue, G., Wang, Y., Guan, X., & Wang, Z. (2022). A combined GA-TS algorithm for two-echelon dynamic vehicle routing with proactive satellite stations. Computers & Industrial Engineering, 164, 107899. https://doi.org/10.1016/j.cie.2021.107899
Yu, X., Zhou, Y., & Liu, X. F. (2020). The two-echelon multi-objective location routing problem inspired by realistic waste collection applications: The composable model and a metaheuristic algorithm. Applied Soft Computing, 94, 106477. https://doi.org/10.1016/j.asoc.2020.106477
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