Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/5384
Title: A biased random-key genetic algorithm for the minimization of open stacks problem
Authors: José Fernando Gonçalves
Resende,MGC
Costa,MD
Issue Date: 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.
URI: http://repositorio.inesctec.pt/handle/123456789/5384
http://dx.doi.org/10.1111/itor.12109
metadata.dc.type: article
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