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(Reference retrieved automatically from SciELO through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPS

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Author(s):
Silvio Alexandre de Araujo [1] ; Kelly Cristina Poldi [2] ; Jim Smith [3]
Total Authors: 3
Affiliation:
[1] Universidade Estadual Paulista. Departamento de Matemática Aplicada - Brasil
[2] Universidade Federal de São Paulo. Instituto de Ciência e Tecnologia - Brasil
[3] University of the West of England. Faculty of Environment and Technology - Reino Unido
Total Affiliations: 3
Document type: Journal article
Source: Pesquisa Operacional; v. 34, n. 2, p. 165-187, 2014-08-00.
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. (AU)

FAPESP's process: 12/00464-4 - Models and resolution methods for the nesting problem
Grantee:Franklina Maria Bragion de Toledo
Support Opportunities: Research Grants - Visiting Researcher Grant - International
FAPESP's process: 11/22647-0 - Lot sizing problems: integrations and solution methods
Grantee:Silvio Alexandre de Araujo
Support Opportunities: Regular Research Grants