Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/36519

TitleSkewed general variable neighborhood search for the location routing scheduling problem
Author(s)Macedo, Rita
Alves, Cláudio
Hanafi, Said
Jarboui, Bassem
Mladenovic, Nenad
Ramos, Bruna
Carvalho, J. M. Valério de
KeywordsLocation
Routing
Scheduling
Variable neighborhood search
Issue dateSep-2015
PublisherElsevier
JournalComputers and Operations Research
CitationMacedo, R., Alves, C., Hanafi, S., Jarboui, B., Mladenović, N., Ramos, B., & de Carvalho, J. V. (2015). Skewed general variable neighborhood search for the location routing scheduling problem. Computers & Operations Research, 61, 143-152
Abstract(s)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.
TypeArticle
URIhttp://hdl.handle.net/1822/36519
DOI10.1016/j.cor.2015.03.011
ISSN0305-0548
Publisher versionhttp://www.sciencedirect.com/science/article/pii/S0305054815000696
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Artigos em revistas internacionais/Papers in international journals

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