Developing a Vehicle Routing Model Considering Effective Criteria for Supporting of Military Units

Document Type : Original Article

Authors

1 Professor, University of Tehran.

2 Associate Professor, Imam Hossein University.

3 Assistant Professor, Imam Hussein University.

Abstract

In this research, a mathematical model of the vehicle routing problem to support military units is presented and solved. To present this model, first, various criteria extracted from the literature review of vehicle routing issues in the field of military, war and crisis are investigated. Then, the criteria that are important for supporting the military units under study are introduced and the mathematical model of the problem based on these criteria is presented. One of the salient features of the current research compared to similar researches is the simultaneous consideration of five effective criteria in supporting the units of this organization, which include "time window for delivery of goods to units", "ability to pick-up and deliver goods on the road transport route", "the heterogeneity of the fleet of road vehicles", "the need to send goods from multi-depot" and "the need to transport several types of goods". Since this is one of the optimization problems in the family of NP-hard problems, GA, PSO and SA algorithms were used to solve the model. In order to validate, the results of these algorithms have been compared with the exact solution results with GAMS software, which shows the proper performance of the proposed genetic algorithm.

Keywords

Main Subjects

References

  1. Adbelhafiz, M., Mostafa, A. & Girard, A. (2010). Vehicle routing problem instances: Application to multi-uav mission planning. AIAA Guidance, Navigation, and Control Conference.
  2. Ahn, N., & Kim, S. (2020). Optimal and heuristic algorithms for the multi-objective vehicle routing problem with drones for military surveillance operations. Journal of Industrial and Management Optimization, Article in press.
  3. Beigi, S. & Hossein-zadeh, E. (2019). A mathematical model for location-routing problem under crisis considering route security. Defensive Future Studies, 13, 89-110.
  4. Crino, J., Moore, J.T., Barnes, J.W. & Nanry, W.P. (2004). Solving the theater distribution vehicle routing and scheduling problem using group theoretic tabu search.Mathematical and Computer Modelling, 39, 599-616.
  5. Du, J., Li, X., Yu., L., Dan, R. & Zhou, J. (2017). Multi-depot vehicle routing problem for hazardous materials transportation: a fuzzy bilevel programming. Information Sciences, 399, 201-218.
  6. Eslami-nia, A. & Azimi, P. (2020). Solving the Electric Vehicle Routing Problem Considering the Vehicle Volume Limitation using a Simulated Annealing Algorithm. Journal of Industrial Management Perspective, 36, 165-188. (In Persian)
  7. Farah-Bakhsh, A. & Behnamian, J. (2020). Solving the CVRP with Reduction to knapsak problem and greedy clustring heuristic method. Journal of Industrial Management Perspective, 36, 89-106. (In Persian)
  8. Farah-Bakhsh, F., Tavakkoli-Moghaddam, R. & Ghazavati, V.R. (2017). Developing a multi-objective mathematical model for hetro-genous vehicle routing problem under crisis situation. Transportation Engineering, 34, 169-187.
  9. Hassanpour, H.A., Mosadegh-khah, M. & Tavakkoli-moghaddam, R. (2008). Solving a multi-objective, multi-depot and stochastic vehicle routing problem by simmulated annealing. Journal of Industrial Engering, 43, 25-36.
  10. Ju, B., Kim, M. & Moon, I. (2021). Vehicle routing problem considering reconnaissance and transportation. Sustainability, 13, 3188.
  11. Li, J., Jing, X. & Tong, C. (2012). Modeling and simulation of VRP in wartime using NSGA II. Chinese Control and Decision Conference (CCDC).
  12. Nikjoo, N. & Javadian, N. (2019). A multi-objective robust optimization logistics model in time of crisis under uncertainty. Journal of Industrial Management Perspective, 32, 121-147. (In Persian)
  13. Nowroozi, P., Hassanpour, H.A. & Kafi, F. (2020). Vehicle routing considering military criteria by hybrid approaches of Heuristic-AHP-TOPSIS (Case study: A transportation unit of a military logistic organization). Logistic Thought Journal, 73, 49-80. (In Persian)
  14. Rashidi-Komaijani, A.R. & Gorani, N. (2015). Vehicle routing problem under crisis. International Conference of Industrial and Management.
  15. Tavakkoli-Moghaddam, R., Alinaghian, M., Nowroozi, N. & Salamat-Bakhsh, A.R. (2011). Solving a new model for vehicle routing problem considering safety in transportation of hazardous materials. Transportation Engineering, 2(3), 223-235.
  16. Tavakkoli-Moghaddam, R. & Kahfi, A. (2015). Solving a multi-depot vehicle routing problem under risk reduction by a multi-objective bat algorithm (MOBA). Transportation Engineering, 6(3), 507-522.
  17. Veisi, O., Heidari, J., Razmi, J. & Sangari, M.S. (2019). Optimization of distribution and supporting model in the supply chain of supporting and procurement system under uncertainy and dynamic situation. Journal of Military Management, 19(2), 81-116.
  18. Wang, C., Mu, D., Zhao, F. & Sutherland, J.W. (2015). A parallel simulated annealing method for the vehicle routing problem with simultaneous pickup–delivery and time windows. Computers & Industrial Engineering, 83, 111-122.
  19. Yancheng, G., Ronggui, H., Xirui, Y., Hongxing, S. & Chang, L. (2010). Improved ant colony algorithm for vehicle scheduling problems of military logistics distribution. International Conference on Logistics Systems and Intelligent Management.
  20. Zeimpekis, V., Kaimakamis, G. & Daras, N.J. (2015). Military Logistics: Research Advances and Future Trends/Computer Science Interfaces Series, 56.
  21. Zhang, S., Mu, D. & Whang, C. (2020). A solution for the full-load collection vehicle routing problem with multiple trips and demands: An Application in Beijing. IEEE ACCESS, 8,
  22. Zhao, T., Huang, J., Shi, J. & Chen, C. (2018). Route planning for military ground vehicles in road networks under uncertain battlefield environment. Journal of Advanced Transportation.

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