References

Adelzadeh, M., Mahdavi Asl, V., & Koosha, M. (2014). A mathematical model and a solving procedure for multi-depot vehicle routing problem with fuzzy time window and heterogeneous vehicle. The international journal of advanced manufacturing technology, 75(5), 793-802. https://doi.org/10.1007/s00170-014-6141-8.
Archetti, C., & Speranza, M. G. (2012). Vehicle routing problems with split deliveries. International transactions in operational research, 19(1-2), 3-22. https://doi.org/10.1111/j.1475-3995.2011.00811.x.
Beheshti, A. K., Hejazi, S. R., & Alinaghian, M. (2015). The vehicle routing problem with multiple prioritized time windows: A case study. Computers & Industrial Engineering, 90, 402-413. https://doi.org/10.1016/j.cie.2015.10.005.
Belhaiza, S. (2016). A game theoretic approach for the real-life multiple-criterion vehicle routing problem with multiple time windows. IEEE Systems Journal, 12(2), 1251-1262. https://doi.org/10.1109/JSYST.2016.2601058.
Belhaiza, S., Hansen, P., & Laporte, G. (2014). A hybrid variable neighborhood tabu search heuristic for the vehicle routing problem with multiple time windows. Computers & Operations Research, 52, 269-281. https://doi.org/10.1016/j.cor.2013.08.010.
Belhaiza, S., M'Hallah, R., & Brahim, G. B. (2017, June). A new hybrid genetic variable neighborhood search heuristic for the vehicle routing problem with multiple time windows. In 2017 IEEE Congress on Evolutionary Computation (CEC) (pp. 1319-1326). IEEE. https://doi.org/10.1109/CEC.2017.7969457.
Bogue, E. T., Ferreira, H. S., Noronha, T. F., & Prins, C. (2020). A column generation and a post optimization VNS heuristic for the vehicle routing problem with multiple time windows. Optimization Letters, 1-17. https://doi.org/10.1007/s11590-019-01530-w.
Bräysy, O., Porkka, P. P., Dullaert, W., Repoussis, P. P., & Tarantilis, C. D. (2009). A well-scalable metaheuristic for the fleet size and mix vehicle routing problem with time windows. Expert Systems with Applications, 36(4), 8460-8475. https://doi.org/10.1016/j.eswa.2008.10.040.
Bräysy, O., Dullaert, W., Hasle, G., Mester, D., & Gendreau, M. (2008). An effective multirestart deterministic annealing metaheuristic for the fleet size and mix vehicle-routing problem with time windows. Transportation Science, 42(3), 371-386. https://doi.org/10.1287/trsc.1070.0217.
Chiang, T. C., & Hsu, W. H. (2014). A knowledge-based evolutionary algorithm for the multiobjective vehicle routing problem with time windows. Computers & Operations Research, 45, 25-37. https://doi.org/10.1016/j.cor.2013.11.014.
Choi, W., & Lee, Y. (2002). A dynamic part-feeding system for an automotive assembly line. Computers & industrial engineering, 43(1-2), 123-134.
Dantzig, G. B., & Ramser, J. H. (1959). The truck dispatching problem. Management science, 6(1), 80-91.
Dondo, R., & Cerdá, J. (2007). A cluster-based optimization approach for the multi-depot heterogeneous fleet vehicle routing problem with time windows. European journal of operational research, 176(3), 1478-1507. https://doi.org/10.1016/j.ejor.2004.07.077.
Fachini, R. F., & Armentano, V. A. (2020). Logic-based Benders decomposition for the heterogeneous fixed fleet vehicle routing problem with time windows. Computers & Industrial Engineering, 148, 106641. https://doi.org/10.1016/j.cie.2020.106641.
El Fallahi, A., Prins, C., & Calvo, R. W. (2008). A memetic algorithm and a tabu search for the multi-compartment vehicle routing problem. Computers & Operations Research, 35(5), 1725-1741. https://doi.org/10.1016/j.cor.2006.10.006.
Favaretto, D., Moretti, E., & Pellegrini, P. (2007). Ant colony system for a VRP with multiple time windows and multiple visits. Journal of Interdisciplinary Mathematics, 10(2), 263-284. https://doi.org/10.1080/09720502.2007.10700491.
Fazlollahtabar, H., & Mahdavi-Amiri, N. (2012). An optimal path in a bi-criteria AGV-based flexible jobshop manufacturing system having uncertain parameters. International Journal of Industrial and Systems Engineering, 13(1), 27-55. https://doi.org/10.1504/IJISE.2013.050544.
Gendreau, M., Laporte, G., Musaraganyi, C., & Taillard, É. D. (1999). A tabu search heuristic for the heterogeneous fleet vehicle routing problem. Computers & Operations Research, 26(12), 1153-1173. https://doi.org/10.1016/S0305-0548(98)00100-2.
Goeke, D., & Schneider, M. (2015). Routing a mixed fleet of electric and conventional vehicles. European Journal of Operational Research, 245(1), 81-99. https://doi.org/10.1016/j.ejor.2015.01.049.
Golden, B., Assad, A., Levy, L., & Gheysens, F. (1984). The fleet size and mix vehicle routing problem. Computers & Operations Research, 11(1), 49-66. https://doi.org/10.1016/0305-0548(84)90007-8.
Guezouli, L., & Abdelhamid, S. (2017). A new multi-criteria solving procedure for multi-depot FSM-VRP with time window. International Journal of Applied Industrial Engineering (IJAIE), 4(1), 1-18. https://doi.org/10.4018/IJAIE.2017010101.
Ho, W., Ho, G. T., Ji, P., & Lau, H. C. (2008). A hybrid genetic algorithm for the multi-depot vehicle routing problem. Engineering applications of artificial intelligence, 21(4), 548-557. https://doi.org/10.1016/j.engappai.2007.06.001.
Ho, Y. C., & Liao, T. W. (2009). Zone design and control for vehicle collision prevention and load balancing in a zone control AGV system. Computers & Industrial Engineering, 56(1), 417-432. https://doi.org/10.1016/j.cie.2008.07.007.
Hoogeboom, M., Dullaert, W., Lai, D., & Vigo, D. (2020). Efficient neighborhood evaluations for the vehicle routing problem with multiple time windows. Transportation Science, 54(2), 400-416. https://doi.org/10.1287/trsc.2019.0912.
Jiang, J., Ng, K. M., Poh, K. L., & Teo, K. M. (2014). Vehicle routing problem with a heterogeneous fleet and time windows. Expert Systems with Applications, 41(8), 3748-3760. https://doi.org/10.1016/j.eswa.2013.11.029.
Jin, J., & Zhang, X. H. (2016). Multi agv scheduling problem in automated container terminal. Journal of Marine Science and Technology, 24(1), 5.
Larsen, R., & Pacino, D. (2019). Fast delta evaluation for the vehicle routing problem with multiple time windows. arXiv preprint arXiv:1905.04114. https://ui.adsabs.harvard.edu/abs/2019arXiv190504114L.
Li, X. Y., Tian, P., & Leung, S. C. (2009). An ant colony optimization metaheuristic hybridized with tabu search for open vehicle routing problems. Journal of the Operational Research Society, 60(7), 1012-1025. https://doi.org/10.1057/palgrave.jors.2602644.
Liu, K., & Zhang, M. (2016, December). Path planning based on simulated annealing ant colony algorithm. In 2016 9th International Symposium on Computational Intelligence and Design (ISCID) (Vol. 2, pp. 461-466). IEEE. https://doi.org/10.1109/ISCID.2016.2114.
Matei, O., Pop, P. C., Sas, J. L., & Chira, C. (2015). An improved immigration memetic algorithm for solving the heterogeneous fixed fleet vehicle routing problem. Neurocomputing, 150, 58-66. https://doi.org/10.1016/j.neucom.2014.02.074.
Paradiso, R., Roberti, R., Laganá, D., & Dullaert, W. (2020). An exact solution framework for multitrip vehicle-routing problems with time windows. Operations Research, 68(1), 180-198. https://doi.org/10.1287/opre.2019.1874.
Paraskevopoulos, D. C., Repoussis, P. P., Tarantilis, C. D., Ioannou, G., & Prastacos, G. P. (2008). A reactive variable neighborhood tabu search for the heterogeneous fleet vehicle routing problem with time windows. Journal of Heuristics, 14(5), 425-455. https://doi.org/10.1007/s10732-007-9045-z.
Salhi, S., Wassan, N., & Hajarat, M. (2013). The fleet size and mix vehicle routing problem with backhauls: Formulation and set partitioning-based heuristics. Transportation Research Part E: Logistics and Transportation Review, 56, 22-35. https://doi.org/10.1016/j.tre.2013.05.005.
Simić, D., Kovačević, I., Svirčević, V., & Simić, S. (2015). Hybrid firefly model in routing heterogeneous fleet of vehicles in logistics distribution. Logic Journal of the IGPL, 23(3), 521-532. https://doi.org/10.1093/jigpal/jzv011.
Simsir, F., & Ekmekci, D. (2019). A metaheuristic solution approach to capacitied vehicle routing and network optimization. Engineering Science and Technology, an International Journal, 22(3), 727-735. https://doi.org/10.1016/j.jestch.2019.01.002.
Stützle, T., & Hoos, H. H. (2000). MAX–MIN ant system. Future generation computer systems, 16(8), 889-914.
Taillard, É., Badeau, P., Gendreau, M., Guertin, F., & Potvin, J. Y. (1997). A tabu search heuristic for the vehicle routing problem with soft time windows. Transportation science, 31(2), 170-186.
Taillard, É. D. (1999). A heuristic column generation method for the heterogeneous fleet VRP. RAIRO-Operations Research, 33(1), 1-14. https://doi.org/10.1051/ro:1999101.
Umar, U. A., Ariffin, M. K. A., Ismail, N., & Tang, S. H. (2015). Hybrid multiobjective genetic algorithms for integrated dynamic scheduling and routing of jobs and automated-guided vehicle (AGV) in flexible manufacturing systems (FMS) environment. The International Journal of Advanced Manufacturing Technology, 81(9), 2123-2141. DOI: 10.1007/s00170-015-7329-2.
Xia, Y., & Fu, Z. (2019a). A tabu search algorithm for distribution network optimization with discrete split deliveries and soft time windows. Cluster Computing, 22(6), 15447-15457. https://doi.org/10.1007/s10586-018-2635-8.
Xia, Y., & Fu, Z. (2019b). Improved tabu search algorithm for the open vehicle routing problem with soft time windows and satisfaction rate. Cluster Computing, 22(4), 8725-8733. https://doi.org/10.1007/s10586-018-1957-x.