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A genetic algorithm for the one-dimensional cutting stock problem with setups

de Araujo, Silvio Alexandre; Poldi, Kelly Cristina; Smith, Jim


Silvio Alexandre de Araujo

Kelly Cristina Poldi

Jim Smith
Professor in Interactive Artificial Intelligence


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. © 2014 Brazilian Operations Research Society.


de Araujo, S. A., Poldi, K. C., & Smith, J. (2014). A genetic algorithm for the one-dimensional cutting stock problem with setups. Pesquisa Operacional, 34(2), 165-187.

Journal Article Type Article
Publication Date Jan 1, 2014
Journal Pesquisa Operacional
Print ISSN 0101-7438
Electronic ISSN 1678-5142
Peer Reviewed Peer Reviewed
Volume 34
Issue 2
Pages 165-187
Keywords evolutionary computation, memetics, applications
Public URL
Publisher URL


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