A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPS

A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPS

Autor Araujo, Silvio Alexandre De Google Scholar
Poldi, Kelly Cristina Google Scholar
Smith, Jim Google Scholar
Instituição Universidade Estadual Paulista (UNESP)
Universidade Federal de São Paulo (UNIFESP)
University of the West of England Faculty of Environment and Technology
Resumo This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting patterns used. A new heuristic method based on the concepts of genetic algorithms is proposed to solve the problem. This heuristic is empirically analyzed by solving randomly generated instances and also practical instances from a chemical-fiber company. The computational results show that the method is efficient and obtains positive results when compared to other methods from the literature.
Assunto integer optimization
cutting stock problem with setups
genetic algorithm
Idioma Inglês
Data 2014-05-01
Publicado em Pesquisa Operacional. Sociedade Brasileira de Pesquisa Operacional, v. 34, n. 2, p. 165-187, 2014.
ISSN 0101-7438 (Sherpa/Romeo)
Editor Sociedade Brasileira de Pesquisa Operacional
Extensão 165-187
Fonte http://dx.doi.org/10.1590/0101-7438.2014.034.02.0165
Direito de acesso Acesso aberto Open Access
Tipo Artigo
SciELO S0101-74382014000200165 (estatísticas na SciELO)
URI http://repositorio.unifesp.br/handle/11600/8367

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