An adaptive large neighbourhood search for the operational integrated production and distribution problem of perishable products

dc.contributor.author Belo Filho,MAF en
dc.contributor.author Pedro Amorim en
dc.contributor.author Bernardo Almada-Lobo en
dc.date.accessioned 2018-01-12T09:59:14Z
dc.date.available 2018-01-12T09:59:14Z
dc.date.issued 2015 en
dc.description.abstract Production 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.identifier.uri http://repositorio.inesctec.pt/handle/123456789/5941
dc.identifier.uri http://dx.doi.org/10.1080/00207543.2015.1010744 en
dc.language eng en
dc.relation 5428 en
dc.relation 5964 en
dc.rights info:eu-repo/semantics/embargoedAccess en
dc.title An adaptive large neighbourhood search for the operational integrated production and distribution problem of perishable products en
dc.type article en
dc.type Publication en
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