Name
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1111/itor.12109 | INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH |
Keywords | Field | DocType |
minimization of open stacks problem, cutting pattern, biased random-key genetic algorithm, random keys | Mathematical optimization,Stack (abstract data type),Computer science,Fitness function,Minification,Local search (optimization),Genetic algorithm | Journal |
Volume | Issue | ISSN |
23 | 1-2 | 0969-6016 |
Citations | PageRank | References |
9 | 0.52 | 22 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Fernando Gonçalves | 1 | 736 | 37.31 |
| Mauricio G. C. Resende | 2 | 3729 | 336.98 |
| miguel dias costa | 3 | 9 | 0.52 |