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

Autor(es)

Silvio Alexandre de Araujo ^[1] ; Kelly Cristina Poldi ^[2] ; Jim Smith ^[3]

Afiliação do(s) autor(es)

^[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

• Tipo de documento: Artigo Científico
• Fonte: Pesquisa Operacional; v. 34, n. 2, p. 165-187, 2014-08-00.

Resumo

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)

• Processo FAPESP: 11/22647-0 - Problemas de dimensionamento de lotes: integrações e métodos de solução
• Beneficiário: Silvio Alexandre de Araujo
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 12/00464-4 - Modelos e métodos de resolução para o problema de corte bidimensional
• Beneficiário: Franklina Maria Bragion de Toledo
• Modalidade de apoio: Auxílio à Pesquisa - Pesquisador Visitante - Internacional