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

• Type: Article in International Scientific Journal
• Date: 2016

Authors

Jose Fernando Goncalves (Author) FEP; Resende, MGC (Author) Other; Costa, MD (Author) Other

Journal

Title: International Transactions in Operational Research

Vol. 23 No. 1-2

Pages: 25-46

ISSN: 0969-6016

Publisher: Wiley-Blackwell

Indexing

ISI Web of Knowledge - 17 Citations

Scopus - 19 Citations

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 22