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

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

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. © 2014 Brazilian Operations Research Society.

• Journal Article Type: Article
• Publication Date: Jan 1, 2014
• Deposit Date: Sep 14, 2015
• Publicly Available Date: Feb 12, 2016
• Journal: Pesquisa Operacional
• Print ISSN: 0101-7438
• Peer Reviewed: Peer Reviewed
• Volume: 34
• Issue: 2
• Pages: 165-187
• DOI: https://doi.org/10.1590/0101-7438.2014.034.02.0165
• Keywords: evolutionary computation, memetics, applications
• Public URL: https://uwe-repository.worktribe.com/output/827404
• Publisher URL: http://dx.doi.org/10.1590/0101-7438.2014.034.02.0165
• Contract Date: Feb 12, 2016