Abstract
This paper studies the multitrip cumulative capacitated vehicle routing problem (mt-CCVRP), a variant of the classical capacitated vehicle routing problem (CVRP). In the mt-CCVRP the objective function becomes the minimization of the sum of arrival times at required nodes and each vehicle may perform more than one trip. Applications of this NP-Hard problem can be found in disaster logistics. This article presents a Multistart Evolutionary Local Search (MS-ELS) that alternates between giant tour and mt-CCVRP solutions, and uses an adapted split procedure and a variable neighborhood descent (VND). The results on two sets of instances show that this approach finds very good results in relatively short computing time compared with a multistart iterated local search which works directly on the mt-CCVRP solution space.
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Rivera, J.C., Afsar, H.M., Prins, C. (2014). Multistart Evolutionary Local Search for a Disaster Relief Problem. In: Legrand, P., Corsini, MM., Hao, JK., Monmarché, N., Lutton, E., Schoenauer, M. (eds) Artificial Evolution. EA 2013. Lecture Notes in Computer Science(), vol 8752. Springer, Cham. https://doi.org/10.1007/978-3-319-11683-9_11
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DOI: https://doi.org/10.1007/978-3-319-11683-9_11
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