Name
Title | ||
|---|---|---|
A hybrid particle swarm optimization algorithm based on space transformation search and a modified velocity model |
Abstract | ||
|---|---|---|
Particle Swarm Optimization (PSO) has shown its fast search speed in many complicated optimization and search problems. However, PSO often easily falls into local optima because the particles would quickly get closer to the best particle. Under these circumstances, the best particle could hardly be improved. This paper proposes a new hybrid PSO (HPSO) to solve this problem by combining space transformation search (STS) with a new modified velocity model. Experimental studies on 8 benchmark functions demonstrate that the HPSO holds good performance in solving both unimodal and multimodal functions optimization problems. |
Year | DOI | Venue |
|---|---|---|
2009 | null | International Journal of Numerical Analysis and Modeling |
Keywords | Field | DocType |
new modified velocity model,new hybrid pso,particle swarm optimization,best particle,complicated optimization,search problem,benchmark function,optimization problem,fast search speed,hybrid particle swarm optimization,space transformation search,evolutionary algorithm,optimization | Particle swarm optimization,Derivative-free optimization,Mathematical optimization,Local optimum,Computer science,Meta-optimization,Algorithm,Multi-swarm optimization,Imperialist competitive algorithm,Optimization problem,Metaheuristic | Conference |
Volume | Issue | ISSN |
9 | 2 | null |
ISBN | Citations | PageRank |
3-642-11841-0 | 4 | 0.40 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu Song | 1 | 356 | 52.74 |
| Zhijian Wu | 2 | 247 | 18.55 |
| Hui Wang | 3 | 277 | 17.29 |
| Zhangxing Chen | 4 | 13 | 2.95 |