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. [ABSTRACT FROM AUTHOR]
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Computers and Operations Research, Elsevier, 2015, 61, pp.143--152. 〈10.1016/j.cor.2015.03.011〉
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https://hal.archives-ouvertes.fr/hal-01592785
Contributeur : Romain Boisselet <>
Soumis le : lundi 25 septembre 2017 - 13:52:13
Dernière modification le : vendredi 7 décembre 2018 - 12:50:03

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Rita Macedo, Claudio Alves, Saã¯d Hanafi, Bassem Jarboui, Nenad Mladenovic, et al.. Skewed general variable neighborhood search for the location routing scheduling problem. Computers and Operations Research, Elsevier, 2015, 61, pp.143--152. 〈10.1016/j.cor.2015.03.011〉. 〈hal-01592785〉

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