Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/5941
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dc.contributor.authorBelo Filho,MAFen
dc.contributor.authorPedro Amorimen
dc.contributor.authorBernardo Almada-Loboen
dc.date.accessioned2018-01-12T09:59:14Z-
dc.date.available2018-01-12T09:59:14Z-
dc.date.issued2015en
dc.identifier.urihttp://repositorio.inesctec.pt/handle/123456789/5941-
dc.identifier.urihttp://dx.doi.org/10.1080/00207543.2015.1010744en
dc.description.abstractProduction and distribution problems with perishable goods are common in many industries. For the sake of the competitiveness of the companies, the supply chain planning of products with restricted lifespan should be addressed with an integrated approach. Particularly, at the operational level, the sizing and scheduling of production lots have to be decided together with vehicle routing decisions to satisfy the customers. However, such joint decisions make the problems hard to solve for industries with a large product portfolio. This paper proposes an adaptive large neighbourhood search (ALNS) framework to tackle the problem. This metaheuristic is well known to be effective for vehicle routing problems. The proposed approach relies on mixed-integer linear programming models and tools. The ALNS outperforms traditional procedures of the literature, namely, exact methods and fix-and-optimize, in terms of quality of the solution and computational time of the algorithms. Nine in ten runs of ALNS yielded better solutions than traditional procedures, outperforming on average 12.7% over the best solutions provided by the latter methods.en
dc.languageengen
dc.relation5428en
dc.relation5964en
dc.rightsinfo:eu-repo/semantics/embargoedAccessen
dc.titleAn adaptive large neighbourhood search for the operational integrated production and distribution problem of perishable productsen
dc.typearticleen
dc.typePublicationen
Appears in Collections:CEGI - Articles in International Journals

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