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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/114164
Title: 
A genetic algorithm for the one-dimensional cutting stock problem with setups
Author(s): 
Institution: 
  • Universidade Estadual Paulista (UNESP)
  • Universidade Federal de São Paulo (UNIFESP)
  • University of the West of England Faculty of Environment and Technology
ISSN: 
0101-7438
Sponsorship: 
  • Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
  • Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
  • Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Abstract: 
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.
Issue Date: 
1-May-2014
Citation: 
Pesquisa Operacional. Sociedade Brasileira de Pesquisa Operacional, v. 34, n. 2, p. 165-187, 2014.
Time Duration: 
165-187
Publisher: 
Sociedade Brasileira de Pesquisa Operacional
Keywords: 
  • integer optimization
  • cutting stock problem with setups
  • genetic algorithm
Source: 
http://dx.doi.org/10.1590/0101-7438.2014.034.02.0165
URI: 
Access Rights: 
Acesso aberto
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/114164
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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