Name
Title | ||
|---|---|---|
Differential Evolution With Composite Trial Vector Generation Strategies and Control Parameters |
Abstract | ||
|---|---|---|
Trial vector generation strategies and control parameters have a significant influence on the performance of differential evolution (DE). This paper studies whether the performance of DE can be improved by combining several effective trial vector generation strategies with some suitable control parameter settings. A novel method, called composite DE (CoDE), has been proposed in this paper. This method uses three trial vector generation strategies and three control parameter settings. It randomly combines them to generate trial vectors. CoDE has been tested on all the CEC2005 contest test instances. Experimental results show that CoDE is very competitive. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TEVC.2010.2087271 | IEEE Trans. Evolutionary Computation |
Keywords | Field | DocType |
trial vector,composite trial vector generation,evolutionary computation,novel method,composite de,global numerical optimization,control parameter,paper study,composite trial vector generation strategies,cec2005 contest test instance,trial vector generation strategy,differential evolution,effective trial vector generation,suitable control parameter setting,control parameters,vectors,control parameter setting,indexing terms,robustness,encoding,convergence,space exploration,optimization | Convergence (routing),Vector control,Mathematical optimization,Evolutionary algorithm,Evolutionary computation,Algorithm,Robustness (computer science),Differential evolution,Vector generation,Mathematics,Encoding (memory) | Journal |
Volume | Issue | ISSN |
15 | 1 | 1089-778X |
Citations | PageRank | References |
462 | 9.41 | 21 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yong Wang | 1 | 920 | 25.54 |
| Zixing Cai | 2 | 1525 | 66.96 |
| Qingfu Zhang | 3 | 7634 | 255.05 |