A biased random-key genetic algorithm for the minimization of open stacks problem

• Tipo: Artigo em Revista Científica Internacional
• Data: 2016

Autores

Jose Fernando Goncalves (Autor) FEP; Resende, MGC (Autor) Outra; Costa, MD (Autor) Outra

Revista

Título: International Transactions in Operational Research

Vol. 23 Nº 1-2

Páginas: 25-46

ISSN: 0969-6016

Editora: Wiley-Blackwell

Indexação

ISI Web of Knowledge - 17 Citações

Scopus - 19 Citações

Outras Informações

ID Authenticus: P-00G-VJN

DOI: 10.1111/itor.12109

Abstract (EN): This paper describes a biased random-key genetic algorithm (BRKGA) for the minimization of the open stacks problem (MOSP). The MOSP arises in a production system scenario, and consists of determining a sequence of cutting patterns that minimize the maximum number of open stacks during the cutting process. The proposed approach combines a BRKGA and a local search procedure for generating the sequence of cutting patterns. A novel fitness function for evaluating the quality of the solutions is also developed. Computational tests are presented using available instances taken from the literature. The high quality of the solutions obtained validate the proposed approach.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 22