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

Authors :
Gonçalves, José Fernando
Resende, Mauricio G. C.
Costa, Miguel Dias
Source :
International Transactions in Operational Research; Jan2016, Vol. 23 Issue 1/2, p25-46, 22p, 5 Diagrams, 15 Charts
Publication Year :
2016

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09696016
Volume :
23
Issue :
1/2
Database :
Complementary Index
Journal :
International Transactions in Operational Research
Publication Type :
Academic Journal
Accession number :
110694846
Full Text :
https://doi.org/10.1111/itor.12109