Single and parallel machine capacitated lotsizing and scheduling: New iterative MIP-based neighborhood search heuristics

• Tipo: Artigo em Revista Científica Internacional
• Data: 2011

Autores

Ross J. W. James (Autor) Outra; Bernardo Almada-Lobo (Autor) FEUP

Revista

Título: Computers and Operations Research

Vol. 38 Nº 12

Páginas: 1816-1825

ISSN: 0305-0548

Editora: Elsevier

Indexação

ISI Web of Knowledge - 55 Citações

Scopus - 73 Citações

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Outras Informações

ID Authenticus: P-002-JGG

DOI: 10.1016/j.cor.2011.02.005

Abstract (EN): We propose a general-purpose heuristic approach combining metaheuristics and mixed integer programming to find high quality solutions to the challenging single- and parallel-machine capacitated lotsizing and scheduling problem with sequence-dependent setup times and costs. Commercial solvers fail to solve even medium-sized instances of this NP-hard problem; therefore, heuristics are required to find competitive solutions. We develop construction, improvement and search heuristics all based on MIP formulations. We then compare the performance of these heuristics with those of two metaheuristics and other MIP-based heuristics that have been proposed in the literature, and to a state-of-the-art commercial solver. A comprehensive set of computational experiments shows the effectiveness and efficiency of the main approach, a stochastic MIP-based local search heuristic, in solving medium to large size problems. Our solution procedures are quite flexible and may easily be adapted to cope with model extensions or to address different optimization problems that arise in practice. (C) 2011 Elsevier Ltd. All rights reserved.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 10