A genetic algorithm for the one-dimensional cutting stock problem with setups
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Data
2014-05-01
Autores
Araujo, Silvio Alexandre de [UNESP]
Poldi, Kelly Cristina
Smith, Jim
Título da Revista
ISSN da Revista
Título de Volume
Editor
Sociedade Brasileira de Pesquisa Operacional
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.
Descrição
Palavras-chave
integer optimization, cutting stock problem with setups, genetic algorithm
Como citar
Pesquisa Operacional. Sociedade Brasileira de Pesquisa Operacional, v. 34, n. 2, p. 165-187, 2014.