Name
Abstract | ||
|---|---|---|
Genetic Algorithms (GA) have been widely used inoperations research andoptimization since first proposed. A typical GAcomprises three stages, the encoding, theselection and the recombination stages. In thiswork, we focus our attention on the selectionstage of GA, and review afew commonly employed selection schemes andtheir associated scalingfunctions. We also examine common problems andsolution methods forsuch selection schemes.We then propose a new selection scheme inspiredby sexual selectionprinciples through female choice selection, andcompare the performance of this new schemewith commonly used selection methods in solvingsome well-known problems including the Royal RoadProblem, the Open Shop Scheduling Problem andthe Job Shop Scheduling Problem. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1023/A:1022692631328 | Artif. Intell. Rev. |
Keywords | Field | DocType |
genetic algorithm,scheduling,selection | Mathematical optimization,Job shop scheduling,Computer science,Scheduling (computing),Flow shop scheduling,Sexual selection,Open-shop scheduling,Mate choice,Artificial intelligence,Genetic algorithm,Machine learning,Encoding (memory) | Journal |
Volume | Issue | ISSN |
19 | 2 | 1573-7462 |
Citations | PageRank | References |
23 | 1.32 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kai Song Goh | 1 | 28 | 2.15 |
| Andrew Lim | 2 | 373 | 21.86 |
| Brian Rodrigues | 3 | 311 | 22.31 |