Name
Title | ||
|---|---|---|
A hybrid algorithm based on fish school search and particle swarm optimization for dynamic problems |
Abstract | ||
|---|---|---|
Swarm Intelligence algorithms have been extensively applied to solve optimization problems. However, some of them, such as Particle Swarm Optimization, may not present the ability to generate diversity after environmental changes. In this paper we propose a hybrid algorithm to overcome this problem by applying a very interesting feature of the Fish School Search algorithm to the Particle Swarm Optimization algorithm, the collective volitive operator. We demonstrated that our proposal presents a better performance when compared to the FSS algorithm and some PSO variations in dynamic environments. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-21524-7_67 | ICSI |
Keywords | Field | DocType |
particle swarm optimization,hybrid algorithm,particle swarm optimization algorithm,pso variation,swarm intelligence algorithm,dynamic problem,dynamic environment,collective volitive operator,better performance,fish school search,fish school search algorithm,fss algorithm | Particle swarm optimization,Mathematical optimization,Search algorithm,Computer science,Swarm intelligence,Meta-optimization,Multi-swarm optimization,Firefly algorithm,Artificial intelligence,Imperialist competitive algorithm,Machine learning,Metaheuristic | Conference |
Volume | ISSN | Citations |
6729 | 0302-9743 | 2 |
PageRank | References | Authors |
0.41 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| George M. Cavalcanti-Júnior | 1 | 2 | 0.75 |
| Carmelo J. A. Bastos-Filho | 2 | 81 | 18.45 |
| Fernando B. Lima-Neto | 3 | 2 | 0.75 |
| Rodrigo M. C. S. Castro | 4 | 5 | 0.80 |