Name
Title | ||
|---|---|---|
Performance comparison of self-adaptive and adaptive differential evolution algorithms |
Abstract | ||
|---|---|---|
Differential evolution (DE) has been shown to be a simple, yet powerful, evolutionary algorithm for global optimization for many real problems. Adaptation, especially self-adaptation, has been found to be highly beneficial for adjusting control parameters, especially when done without any user interaction. This paper presents differential evolution algorithms, which use different adaptive or self-adaptive mechanisms applied to the control parameters. Detailed performance comparisons of these algorithms on the benchmark functions are outlined. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/s00500-006-0124-0 | Soft Comput. |
Keywords | Field | DocType |
Differential evolution,Control parameter,Fitness function,Optimization,Self-adaptation | Evolutionary algorithm,Computer science,Evolution strategy,CMA-ES,Artificial intelligence,Mathematical optimization,Global optimization,Meta-optimization,Evolutionary computation,Algorithm,Fitness function,Differential evolution,Machine learning | Journal |
Volume | Issue | ISSN |
11 | 7 | 1432-7643 |
Citations | PageRank | References |
108 | 5.54 | 13 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Janez Brest | 1 | 2190 | 90.76 |
| Borko Bošković | 2 | 343 | 17.09 |
| Sašo Greiner | 3 | 1203 | 43.68 |
| Viljem Žumer | 4 | 309 | 19.95 |
| Mirjam Sepesy Maučec | 5 | 506 | 26.34 |