Name
Abstract | ||
|---|---|---|
Standard particle swarm optimization 2011 (SPSO2011) is a major improvement of the original particle swarm optimization (PSO) with its adaptive random topology and rotational invariance. Its overall performance has also been improved considerably from the original PSO algorithm, but further improvement is still possible. This study attempts to enhance the exploration ability of SPSO2011 further. The enhancement method conditionally introduces a new genetic mechanism to improve the personal best condition of each particle. This conditional event is called an event-triggered mechanism. Moreover, the new genetic mechanism is utilized to crossover, mutate, and select an improved offspring to improve the condition of the cognitive component and indirectly enhance the exploration ability. The proposed algorithm is called genetic mechanism-enhanced SPSO2011 (SPSO2011_GM). SPSO2011_GM is empirically analyzed with 42 benchmark functions. Results confirm the efficiency of the proposed enhancement method and verify the convergence, exploration, reliability, and scalability of the method. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s00500-017-2724-2 | Soft Comput. |
Keywords | Field | DocType |
Standard particle swarm optimization 2011, Genetic mechanism, Event-triggered mechanism, Cognitive component, Exploration ability | Random topology,Particle swarm optimization,Convergence (routing),Rotational invariance,Mathematical optimization,Crossover,Computer science,Meta-optimization,Multi-swarm optimization,Artificial intelligence,Machine learning,Scalability | Journal |
Volume | Issue | ISSN |
22 | 21 | 1432-7643 |
Citations | PageRank | References |
0 | 0.34 | 16 |
Authors | ||
2 | ||