A genetic algorithm for the one-dimensional cutting stock problem with setups
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Date
Advisor
Coadvisor
Graduate program
Undergraduate course
Journal Title
Journal ISSN
Volume Title
Publisher
Sociedade Brasileira de Pesquisa Operacional
Type
Article
Access right
Acesso aberto
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.
Description
Keywords
integer optimization, cutting stock problem with setups, genetic algorithm
Language
English
Citation
Pesquisa Operacional. Sociedade Brasileira de Pesquisa Operacional, v. 34, n. 2, p. 165-187, 2014.
