Study of the Time Windows Range Impact on Vehicle Routing Problem
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-52723-4_13
Reference14 articles.
1. Ojeda Rios, B. H., Xavier, E. C., Miyazawa, F. K., Amorim, P., Curcio, E., & Santos, M. J. (2021). Recent dynamic vehicle routing problems: A survey. Computers & Industrial Engineering, 160, 107604.
2. RamachandranPillai, R., & Arock, M. (2021). Spiking neural firefly optimization scheme for the capacitated dynamic vehicle routing problem with time windows. Neural Computing and Applications, 33(1), 409–432.
3. Kumar, S. N., & Panneerselvam, R. (2012). A survey on the vehicle routing problem and its variants. Intelligent Information Management, 4(3), 66–74.
4. Okulewicz, M., & Mandziuk, J. (2019). A metaheuristic approach to solve dynamic vehicle routing problem in continuous search space. Swarm and Evolutionary Computation, 48, 44–61.
5. Zhang, H., Ge, H., Yang, J., & Tong, Y. (2022). Review of vehicle routing problems: Models, classification and solving algorithms. Archives of Computational Methods in Engineering, 29(1), 195–221.
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