Abstract
The competition between companies requires finding the optimized vehicle routing, for this reason researches are more and more interested in transportation problems, this article attempts to address a practical variant of the vehicle routing problem (VRP), known as the VRP with soft time windows (VRPSTW), where deliveries are still possible outside the time windows, that often arise in practice.
Industrial problems have several antagonist objectives to optimize simultaneously, so we propose an improved multiobjective local search (MOLS) based on a hybrid approach, that simultaneously minimizes the transportation costs by producing better planning using a fleet of vehicles, and improve the quality of service by reducing the delay time for each customer and reduce time loss by increasing the stopping time for each vehicle. The algorithm is applied to a standard benchmark problem set, and expected to achieve competitive results compared with previously published studies.
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Bouchra, B., Btissam, D., Mohammad, C. (2018). Multiobjective Local Search Based Hybrid Algorithm for Vehicle Routing Problem with Soft Time Windows. In: Tabii, Y., Lazaar, M., Al Achhab, M., Enneya, N. (eds) Big Data, Cloud and Applications. BDCA 2018. Communications in Computer and Information Science, vol 872. Springer, Cham. https://doi.org/10.1007/978-3-319-96292-4_25
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