Name
Abstract | ||
|---|---|---|
Because different optimization algorithms have different search behaviors and advantages, hybrid strategy is one of the main research directions to improve the performance of PSO. Inspired by this idea, a dynamic multi-swarm differential learning particle swarm optimizer (DMSDL-PSO) is proposed in this paper. We propose a novel method to merge the differential evolution operator into each sub-swarm of the DMSDL-PSO. Combining the exploration capability of the differential mutation and employing Quasi-Newton method as a local searcher to enhance the exploitation capability, DMSDL-PSO has a good exploration and exploitation capability. According to the characteristics of the DMSDL-PSO, three modified differential mutation operators are discussed. Differential mutation is adopted for the personal historically best particle. Because the velocity updating equation of the particles in PSO has some shortcomings, a modified velocity updating equation is adopted in DMSDL-PSO. In DMSDL-PSO, in which the particles are divided into several small and dynamic sub-swarms. The dynamic change of sub-swarms can promote the information exchange of the whole swarm. In order to test the performance of DMSDL-PSO, 41 benchmark functions are adopted. Lots of numerical experiments are conducted to compare DMSDL-PSO with other popular algorithms. The numerical results demonstrate that DMSDL-PSO performs better on some benchmark functions. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.swevo.2017.10.004 | Swarm and Evolutionary Computation |
Keywords | Field | DocType |
Swarm intelligence,Particle swarm optimization,Dynamic sub-swarms,Differential mutation | Particle swarm optimization,Mathematical optimization,Swarm behaviour,Computer science,Information exchange,Swarm intelligence,Differential evolution,Multi-swarm optimization,Operator (computer programming),Particle swarm optimizer | Journal |
Volume | ISSN | Citations |
39 | 2210-6502 | 8 |
PageRank | References | Authors |
0.41 | 41 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yonggang Chen | 1 | 267 | 20.44 |
| Lixiang Li | 2 | 533 | 46.82 |
| Haipeng Peng | 3 | 466 | 37.86 |
| Jinghua Xiao | 4 | 231 | 18.17 |
| Qingtao Wu | 5 | 70 | 19.88 |