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• W3121330861 endingPage "105132" @default.
• W3121330861 startingPage "105132" @default.
• W3121330861 abstract "The soft-clustered vehicle-routing problem (SoftCluVRP) is a variant of the classical capacitated vehicle-routing problem. Customers are partitioned into clusters and all customers of the same cluster must be served by the same vehicle. In this paper, we present a large multiple neighborhood search for the SoftCluVRP. We design and analyze multiple cluster destroy and repair operators as well as two post-optimization components, which are both based on variable neighborhood descent. The first allows inter-route exchanges of complete clusters, while the second searches for intra-route improvements by combining classical neighborhoods (2-opt, Or-opt, double-bridge) and the Balas-Simonetti neighborhood. Computational experiments show that our algorithm clearly outperforms the only existing heuristic approach from the literature. By solving benchmark instances, we provide 130 new best solutions for 220 medium-sized instances with up to 483 customers and prove 12 of them to be optimal. Furthermore, we describe a straightforward adaption of our algorithm to the clustered vehicle-routing problem, a variant of the SoftCluVRP." @default.
• W3121330861 created "2021-02-01" @default.
• W3121330861 creator A5043030849 @default.
• W3121330861 date "2021-05-01" @default.
• W3121330861 modified "2023-10-01" @default.
• W3121330861 title "Large multiple neighborhood search for the soft-clustered vehicle-routing problem" @default.
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• W3121330861 doi "https://doi.org/10.1016/j.cor.2020.105132" @default.
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