Convoy movement problem for combat supply distribution network on the battlefield

References

• Akbari, F., Valizadeh, J., & Hafezalkotob, A. (2022). Robust cooperative planning of relief logistics operations under demand uncertainty: A case study on a possible earthquake in Tehran. International Journal of Systems Science: Operations and Logistics, 9(3), 405–428. https://doi.org/10.1080/23302674.2021.1914767
   Google Scholar
• Akgün, İ, & Erdal, H. (2019). Solving an ammunition distribution network design problem using multi-objective mathematical modeling, combined AHP-TOPSIS, and GIS. Computers and Industrial Engineering, 129(January), 512–528. https://doi.org/10.1016/j.cie.2019.02.004
   Google Scholar
• Boschetti, M. A., Maniezzo, V., Roffilli, M., & Bolufé Röhler, A. (2009). Matheuristics: Optimization, simulation and control. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5818 LNCS, 171–177. https://doi.org/10.1007/978-3-642-04918-7_13
   Google Scholar
• Bovet, J., Constantin, C., & de Werra, D. (1991). A convoy scheduling problem. Discrete Applied Mathematics, 30(1), 1–14. https://doi.org/10.1016/0166-218X(91)90009-L
   Web of Science ®Google Scholar
• Chardaire, P., McKeown, G. P., Verity-Harrison, S. A., & Richardson, S. B. (2005). Solving a time-space network formulation for the convoy movement problem. Operations Research, 53(2), 219–230. https://doi.org/10.1287/opre.1040.0183
   Web of Science ®Google Scholar
• Cummings, N. (1999). How OR helped pacify Bosnia. OR Newsletter (Oper. Res. Soc.), 342, 15–17.
   Google Scholar
• Delfani, F., Kazemi, A., SeyedHosseini, S. M., & Niaki, S. T. A. (2021). A novel robust possibilistic programming approach for the hazardous waste location-routing problem considering the risks of transportation and population. International Journal of Systems Science: Operations and Logistics, 8(4), 383–395. https://doi.org/10.1080/23302674.2020.1781954
   Google Scholar
• Goldstein, D., Shehab, T., Casse, J., & Lin, H. C. (2010). On the formulation and solution of the convoy routing problem. Transportation Research Part E: Logistics and Transportation Review, 46(4), 520–533. https://doi.org/10.1016/j.tre.2009.04.003
   Web of Science ®Google Scholar
• Gopalan, R. (2015). Computational complexity of convoy movement planning problems. Mathematical Methods of Operations Research, 82(1), 31–60. https://doi.org/10.1007/s00186-015-0503-3
   Web of Science ®Google Scholar
• Gopalan, R., & Narayanaswamy, N. S. (2009). Analysis of algorithms for an online version of the convoy movement problem. Journal of the Operational Research Society, 60(9), 1230–1236. https://doi.org/10.1057/palgrave.jors.2602612
   Web of Science ®Google Scholar
• Homsi, G., Jordan, J., Martello, S., & Monaci, M. (2021). The assignment and loading transportation problem. European Journal of Operational Research, 289(3), 999–1007. https://doi.org/10.1016/j.ejor.2019.07.039
   Web of Science ®Google Scholar
• Kim, Y. J., & Do Chung, B. (2023). Energy consumption optimization for the electric vehicle routing problem with state-of-charge-dependent discharging rates. Journal of Cleaner Production, 385, 135703.
   Web of Science ®Google Scholar
• Kress, M. (2002). Operational Logistics. In Operational Logistics, https://doi.org/10.1007/978-1-4615-1085-7
   Google Scholar
• Lai, C. M. (2019). Integrating simplified swarm optimization with AHP for solving capacitated military logistic depot location problem. Applied Soft Computing Journal, 78, 1–12. https://doi.org/10.1016/j.asoc.2019.02.016
   Web of Science ®Google Scholar
• Maniamkot, A. J., Ram Kumar, P. N., Krishnamoorthy, M., Mokhtar, H., & Rajagopalan, S. (2020). Hybridised ant colony optimisation for convoy movement problem. Annals of Operations Research, https://doi.org/10.1007/s10479-020-03846-8
   Web of Science ®Google Scholar
• Marufuzzaman, M., Nur, F., Bednar, A. E., & Cowan, M. (2020). Enhancing Benders decomposition algorithm to solve a combat logistics problem. OR Spectrum, 42(1), 161–198. https://doi.org/10.1007/s00291-019-00571-y
   Web of Science ®Google Scholar
• Mokhtar, H., Krishnamoorthy, M., Dayama, N. R., & Kumar, P. N. R. (2020). New approaches for solving the convoy movement problem. Transportation Research Part E: Logistics and Transportation Review, 133(October 2018), 101802. https://doi.org/10.1016/j.tre.2019.10.007
   Google Scholar
• Ou-Yang, C., Hanyata, T. B., & Samadhi, T. M. A. A. (2016). Hybrid self-adaptive-velocity particle swarm optimisation-Cooper heuristic for the facility location allocation problem in Jakarta. International Journal of Systems Science: Operations and Logistics, 3(2), 63–78. https://doi.org/10.1080/23302674.2015.1029565
   Google Scholar
• Ram Kumar, P. N., & Narendran, T. T. (2008). Integer programming formulation for convoy movement problem. International Journal of Intelligent Defence Support Systems, 1(3), 177. https://doi.org/10.1504/ijidss.2008.023006
   Google Scholar
• Ram Kumar, P. N., & Narendran, T. T. (2009). A mathematical approach for variable speed convoy movement problem(CMP). Defense and Security Analysis, 25(2), 137–155. https://doi.org/10.1080/14751790902985165
   Google Scholar
• Ram Kumar, P. N., & Narendran, T. T. (2011). On the usage of Lagrangean Relaxation for the convoy movement problem. Journal of the Operational Research Society, 62(4), 722–728. https://doi.org/10.1057/jors.2010.4
   Web of Science ®Google Scholar
• Ram Kumar, P. N., Narendran, T. T., & Sivakumar, A. I. (2009). Bi-criteria convoy movement problem. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 6(3), 151–164. https://doi.org/10.1177/1548512909348233
   Google Scholar
• Robinson, E. M., & Leiss, E. L. (2006). Applying genetic algorithms to convoy scheduling. IFIP International Federation for Information Processing, 217, 315–323. https://doi.org/10.1007/978-0-387-34747-9_33
   Google Scholar
• Sadeghnejad-Barkousaraie, A., Batta, R., & Sudit, M. (2017). Convoy movement problem: A civilian perspective. Journal of the Operational Research Society, 68(1), 14–33. https://doi.org/10.1057/s41274-016-0001-x
   Web of Science ®Google Scholar
• Thangarajoo, R., & Lau, H. C. (2010). Distributed route planning and scheduling via hybrid conflict resolution. Proceedings - 2010 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2010, 2, 374–378. https://doi.org/10.1109/WI-IAT.2010.257
   Google Scholar
• Tuson, A. L., & Harrison, S. A. (2005). Problem difficulty of real instances of convoy planning. Journal of the Operational Research Society, 56(7), 763–775. https://doi.org/10.1057/palgrave.jors.2601863
   Web of Science ®Google Scholar
• Wang, Y., Peng, S., Zhou, X., Mahmoudi, M., & Zhen, L. (2020a). Green logistics location-routing problem with eco-packages. Transportation Research Part E: Logistics and Transportation Review, 143(August), 102118. https://doi.org/10.1016/j.tre.2020.102118
   Google Scholar
• Wang, Y., Wang, Z., Hu, X., Xue, G., & Guan, X. (2022). Truck–drone hybrid routing problem with time-dependent road travel time. Transportation Research Part C: Emerging Technologies, 144(September), 103901. https://doi.org/10.1016/j.trc.2022.103901
   Web of Science ®Google Scholar
• Wang, Y., Yuan, Y., Guan, X., Xu, M., Wang, L., Wang, H., & Liu, Y. (2020b). Collaborative two-echelon multicenter vehicle routing optimization based on state–space–time network representation. Journal of Cleaner Production, 258, 120590. https://doi.org/10.1016/j.jclepro.2020.120590
   Web of Science ®Google Scholar