MULTI-DEPOT VEHICLE ROUTING PROBLEM WITH DRONE COLLABORATION IN HUMANITARIAN LOGISTIC

Abstract

Routing problems are used in many areas to obtain the most appropriate results in terms of time and cost. An attempt is made to address the issue by formulating mathematical models that incorporate multiple variables such as capacity, time, cost, and demand, tailored to the specific area of application. Natural disasters are one of these applications. In natural disasters, especially time management is a critical issue. For this reason, routing models play a crucial role in delivering aid to disaster victims and transporting disaster victims to hospitals. In this study, a mathematical model is proposed to be applied in post-disaster humanitarian aid logistics. The model, which aims to minimize the total distribution time, also considers the distribution of perishable commodities. Drones are integrated into this operational framework to facilitate the dissemination of perishable commodities. Thus, a new mathematical model for the multi-depot vehicle routing problem, which includes both truck-drone collaboration and perishable commodities, has been introduced to the literature. The proposed model is solved with an illustrative example using GAMS/CPLEX software and the results are tested.

Keywords

• Drone-Truck Collaboration
• Humanitarian Logistic
• Multi-Depot Vehicle Routing Problem
• Perishable Commodities

References

1. Bhuiyan, T. H., Walker, V., Roni, M., & Ahmed, I. (2024). Aerial drone fleet deployment optimization with endogenous battery replacements for direct delivery of time-sensitive products. Expert Systems with Applications, 252, 124172. https://doi.org/10.1016/j.eswa.2024.124172
2. Calamoneri, T., Corò, F., & Mancini, S. (2022). Multi-Depot Multi-Trip Vehicle Routing with Total Completion Time Minimization (arXiv:2207.06155). arXiv. http://arxiv.org/abs/2207.06155
3. Diabat, A., Jabbarzadeh, A., & Khosrojerdi, A. (2019). A perishable product supply chain network design problem with reliability and disruption considerations. International Journal of Production Economics, 212, 125-138. https://doi.org/10.1016/j.ijpe.2018.09.018
4. Habib, D., Jamal, H., & Khan, S. A. (2013). Employing Multiple Unmanned Aerial Vehicles for Co-Operative Path Planning. International Journal of Advanced Robotic Systems, 10(5), 235https://doi.org/10.5772/56286
5. Haller, J. R. (t.y.). Expanding Optimization of Energy Efficient UAV Routing in Support of Marine Corps Expeditionary Advanced Base Operations with Multiple Supply Depots.
6. Hamid, M., Nasiri, M. M., & Rabbani, M. (2023). A mixed closed-open multi-depot routing and scheduling problem for homemade meal delivery incorporating drone and crowd-sourced fleet: A self-adaptive hyper-heuristic approach. Engineering Applications of Artificial Intelligence, 120, 105876. https://doi.org/10.1016/j.engappai.2023.105876
7. Kim, S. J., Lim, G. J., Cho, J., & Côté, M. J. (2017). Drone-Aided Healthcare Services for Patients with Chronic Diseases in Rural Areas. Journal of Intelligent & Robotic Systems, 88(1), 163-180. https://doi.org/10.1007/s10846-017-0548-z
8. Laporte, G. (1992). The vehicle routing problem: An overview of exact and approximate algorithms. European Journal of Operational Research, 59(3), 345-358. https://doi.org/10.1016/0377-2217(92)90192-C

9. Li, X., Li, P., Zhao, Y., Zhang, L., & Dong, Y. (2021). A Hybrid Large Neighborhood Search Algorithm for Solving the Multi Depot UAV Swarm Routing Problem. IEEE Access, 9, 104115-104126. https://doi.org/10.1109/ACCESS.2021.3098863
10. Lichau, S., Sadykov, R., François, J., & Dupas, R. (2024). A Branch-Cut-And-Price Approach for the Two-Echelon Vehicle Routing Problem with Drones. https://doi.org/10.2139/ssrn.4865970
11. Liu, H., Wu, G., Yuan, Y., Wang, D., Zheng, L., & Zhou, W. (2024). An iterative two-phase optimization method for heterogeneous multi-drone routing problem considering differentiated demands. Complex & Intelligent Systems. https://doi.org/10.1007/s40747-024-01472-6
12. Lu, S.-H., Benaglia, M. F., Nguyen, A.-T., Rivera, E. R., & Cheng, J.-W. (2024). Vehicle routing problem with drones as an aid for epidemic relief. International Journal of Shipping and Transport Logistics. https://www.inderscienceonline.com/doi/10.1504/IJSTL.2024.139062
13. Manyam, S. G., Rasmussen, S., Casbeer, D. W., Kalyanam, K., & Manickam, S. (2017). Multi-UAV routing for persistent intelligence surveillance & reconnaissance missions. 2017 International Conference on Unmanned Aircraft Systems (ICUAS), 573-580. https://doi.org/10.1109/ICUAS.2017.7991314
14. Mavrouli, M., Mavroulis, S., Lekkas, E., & Tsakris, A. (2023). The Impact of Earthquakes on Public Health: A Narrative Review of Infectious Diseases in the Post-Disaster Period Aiming to Disaster Risk Reduction. Microorganisms, 11(2), 419. https://doi.org/10.3390/microorganisms11020419
15. Rashidzadeh, E., Hadji Molana, S. M., Soltani, R., & Hafezalkotob, A. (2021). Assessing the sustainability of using drone technology for last-mile delivery in a blood supply chain. Journal of Modelling in Management, 16(4), 1376-1402. https://doi.org/10.1108/JM2-09-2020-0241
16. Rathinam, S., & Sengupta, R. (2006). Lower and Upper Bounds for a Multiple Depot UAV Routing Problem. Proceedings of the 45th IEEE Conference on Decision and Control, 5287-5292. https://doi.org/10.1109/CDC.2006.377732
17. Song, B. D., & Ko, Y. D. (2016). A vehicle routing problem of both refrigerated- and general-type vehicles for perishable food products delivery. Journal of Food Engineering, 169, 61-71. https://doi.org/10.1016/j.jfoodeng.2015.08.027
18. Stodola, P., & Kutěj, L. (2024). Multi-Depot Vehicle Routing Problem with Drones: Mathematical formulation, solution algorithm and experiments. Expert Systems with Applications, 241, 122483. https://doi.org/10.1016/j.eswa.2023.122483
19. Tan, Q., Zhong, S., Qu, R., Li, Y., Zhou, P., Lo, H. K., & Zhang, X. (2024). Low-Noise Flight Path Planning of Drones Based on a Virtual Flight Noise Simulator: A Vehicle Routing Problem. IEEE Intelligent Transportation Systems Magazine, 2-17. https://doi.org/10.1109/MITS.2024.3396430
20. Walika, M., Moitinho De Almeida, M., Castro Delgado, R., & Arcos González, P. (2023). Outbreaks Following Natural Disasters: A Review of the Literature. Disaster Medicine and Public Health Preparedness, 17, e444. https://doi.org/10.1017/dmp.2023.96