Abstract
Vehicle routing problem with so many restraints are attaining intensively significance. Because of present day needs like fast and furious delivery, in particular, dynamic variant of the issue are getting much preponderance. In DVRP, customer demands are unacquainted and are revealed posterior taking certain discretion. Another different kind dynamic pickup and delivery approach of VRP occurs during new clients come out in the passage after the departure. DVRP are much influencing and out-daring explication of VRP. The objective of this paper is to implement a computational intelligence based algorithms to extricate DVRP. Computational intelligence can potentially optimize the variant of VRP and endue extremely emulative extrication.
Keyword: Vehicle Routing Problem (VRP), Dynamic Vehicle Routing Problem (DVRP), Computational Intelligence, Ant Colony Optimization.
1) Xu, H., Pu, P., and Duan, F.(2018). Dynamic Vehicle Routing Problems with Enhanced Ant Colony Optimization. Hindawi Discrete Dynamics in Nature and Society,https://doi.org/10.1155/2018/1295485.
2) Montemanni, R., Gambardella, L.M., Rizzoli, A.E., and Donati, A.V.(2005). Ant Colony System for a Dynamic Vehicle Routing Problem. Journal of Combinatorial Optimization , volume 10, 327–343.
3) Mavrovouniotis, M., and Yang, S. (2013). Dynamic Vehicle Routing: A Memetic Ant Colony Optimization Approach. Studies in Computational Intelligence, vol 505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39304-4_11
4) Yang, Z., van, Osta, J.P., van, Veen, B., van, Krevelen, R., van, Klaveren, R., Stam, A., Kok, J., Bäck, T., and Emmerich, M.(2016). Dynamic vehicle routing with time windows in theory and practice. Natural Computing, 16(1), 119-134. DOI: 10.1007/s11047-016-9550-9
5) Naqvi, N.Z., Matheru, H.K., and Chadha, K.(2011). Review Of Ant Colony Optimization Algorithms On Vehicle Routing Problems And Introduction To Estimation-Based ACO. International Conference on Environment Science and Engineering IPCBEE, Volume 8.
6) Xiang, X., Qiu, J., Xiao, J., Zhang, X.(2020) . Demand coverage diversity based ant colony optimization for dynamic vehicle routing problems. Engineering Applications of Artificial Intelligence, Volume 91, 103582. https://doi.org/10.1016/j.engappai.2020.103582
7) Mavrovouniotis, M., and Yang, S.(2015). Ant algorithms with immigrants schemes for the dynamic vehicle routing problem. Information Sciences 294, 456–477. http://dx.doi.org/10.1016/j.ins.2014.10.002
8) Euchi, J., Yassine, A., Chabchoub, H.(2014). The dynamic vehicle routing problem: Solution with Hybrid metaheuristic approach. Swarm and Evolutionary Computation, http://dx.doi.org/10.1016/j.swevo.2014.12.003
9) Kuo, R.J., Wibowo, B.S., Zulvia, F.E. (2016). Application of a fuzzy ant colony system to solve the dynamic vehicle routing problem with uncertain service time. Applied Mathematical Modelling(2016) 1–12. http://dx.doi.org/10.1016/j.apm.2016.06.025
10) Veen, B. V., Emmerich, M., Yang, Z., B¨ack, T., and Kok, J. (2013). Ant Colony Algorithms for the Dynamic Vehicle Routing Problem with Time Windows. 5th International Work Conference on the Interplay Between Natural and Artificial Computation. DOI: 10.1007/978-3-642-38622-0_1
11) Gao, S., Wang, Y., Cheng, J., Inazumi, Y., Tang Zheng (2016). Ant colony optimization with clustering for solving the dynamic location routing problem. Applied Mathematics and Computation. http://dx.doi.org/10.1016/j.amc.2016.03.035