Abstract
The Dynamic Vehicle Routing Problem (DVRP) is a variant of the VRP that considers dynamic customer requests. The aim of the problem is to determine a set of routes to minimize the total travel distance. To solve this problem, we propose a Variable Neighbourhood Search (VNS) algorithm, in which eight neighborhood structures are designed to find the optimal routes for a fleet of vehicles serving a given customers without violating any constraints. The proposed algorithm was tested on benchmark instances. Numerical results indicate that the performance of the proposed method is comparable to that reported in the literature.
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References
Chen, B., Qu, R., Bai, R., Laesanklang, W.: A variable neighborhood search algorithm with reinforcement learning for a real-life periodic vehicle routing problem with time windows and open routes. RAIRO - Operations Research (2019)
Karakostas, P., Sifaleras, A., Georgiadis, M.C.: Adaptive variable neighborhood search solution methods for the fleet size and mix pollution location-inventory-routing problem. Exp. Syst. Appl. 153, 113444 (2020)
Tayachi, D., Boukadi, H.: A variable neighborhood search to reduce carbon dioxide emissions in the capacitated vehicle routing problem. In: 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT) (2019)
Srianan, T., Sangsawang, O.: A hybrid variable neighborhood search path-relinking for solving the capacitated single allocation hub location problem (2019)
Kilby, P., Prosser, P., Shaw, P.: Dynamic VRPs: A Study of Scenarios (2002)
Mladenovi, N., Hansen, P.: Variable neighborhood search. Comput. Oper. Res. 24, 1097–1100 (1997)
Abdallah, A.M.F.M., Essam, D.L., Sarker, R.A.: On solving periodic re-optimization dynamic vehicle routing problems. Appl. Soft Comput. 55, 1–2 (2017)
Khouadjia, M.R., Sarasola, B., Alba, E., Jourdan, L., Talbi, E.G.: A comparative study between dynamic adapted PSO and VNS for the vehicle routing problem with dynamic requests. Appl. Soft Comput. J. 12, 1426–1439 (2012)
Liu, M., Shen, Y., Shi, Y.: A hybrid brain storm optimization algorithm for dynamic vehicle routing problem. In: Tan, Y., Shi, Y., Tuba, M. (eds.) Advances in Swarm Intelligence, pp. 251–258. Springer, Cham (2020)
Acknowledgements
This work is supported by the Yanling Youqing program of Lingnan Normal University, the Competitive Allocation of Special Funds for Science and Technology Innovation Strategy in Guangdong Province of China (No. 2018A06001), the Post-doctoral research support project of Harbin Commercial University (No. 2017BSH015) and the PhD Research Startup Foundation of Guangdong Ocean University (No. R20005).
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Chen, S., Yin, Y., Chen, B., Gao, Y., Yang, J. (2021). A Variable Neighbourhood Search Algorithm for Solving Dynamic Vehicle Routing Problem Under Industry 4.0. In: Wang, Y., Martinsen, K., Yu, T., Wang, K. (eds) Advanced Manufacturing and Automation X. IWAMA 2020. Lecture Notes in Electrical Engineering, vol 737. Springer, Singapore. https://doi.org/10.1007/978-981-33-6318-2_83
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DOI: https://doi.org/10.1007/978-981-33-6318-2_83
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