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

• Tipo: Artigo em Revista Científica Internacional
• Data: 2015

Autores

Pedro Amorim (Autor) FEUP; Bernardo Almada Lobo (Autor) FEUP; Marcio Belo Filho (Autor) FEUP

Revista

Título: International Journal of Production Research

Vol. 53

Páginas: 6040-6058

ISSN: 0020-7543

Editora: Taylor & Francis

Indexação

ISI Web of Knowledge - 41 Citações

ISI Web of Science

Scopus - 51 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias

CORDIS: Ciências Tecnológicas

Projetos Associados

BESTCASE-RL2 - Smart Manufacturing and Logistics

Outras Informações

ID Authenticus: P-00G-F7D

DOI: 10.1080/00207543.2015.1010744

Resumo (PT): 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 adaptive large neighbourhood search outperforms traditional procedures of the literature, namely exact methods and x-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 and the best solution value found by the latter methods 12:7% greater than the former, on average.

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 19