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Skewed general variable neighborhood search for the location routing scheduling problem

Abstract : The integrated location routing scheduling problem is a variant of the well-known location routing problem. The location routing problem consists in selecting a set of depots to open and in building a set of routes from these depots, to serve a set of customers at minimum cost. In this variant, a vehicle can perform more than a single route in the planning period. As a consequence, the routes have to be scheduled within the workdays of each vehicle. The problem arises typically when routes are constrained to have a short duration. It happens for example within the boundaries of small geographic areas or in the transportation of perishable goods. In this paper, we propose a skewed general variable neighborhood search based heuristic to solve it. The algorithm is tested extensively and we show that it is efficient and provides the proven optimal solution in a significant number of cases. Moreover, it clearly outperforms a multi-start VND based heuristic that uses the same neighborhood structures.
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https://hal-uphf.archives-ouvertes.fr/hal-03385354
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Submitted on : Tuesday, October 19, 2021 - 2:39:20 PM
Last modification on : Thursday, October 21, 2021 - 5:02:27 AM

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Rita Macedo, Claudio Alves, Said Hanafi, Bassem Jarboui, Nenad Mladenovic. Skewed general variable neighborhood search for the location routing scheduling problem. MIC'2015, The 11th edition of the Metaheuristics International Conference, Jun 2015, Agadir, Morocco. pp.143-152, ⟨10.1016/j.cor.2015.03.011⟩. ⟨hal-03385354⟩

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