Name
Abstract | ||
|---|---|---|
In this paper, we choose to compare four methods for controlling particle position when it violates the search space boundaries and the impact on the performance of Particle Swarm Optimization algorithm (PSO). The methods are: hard borders, soft borders, random position and spherical universe. The goal is to compare the performance of these methods for the classical version of PSO and popular modification - the Attractive and Repulsive Particle Swarm Optimization (ARPSO). The experiments were carried out according to CEC benchmark rules and statistically evaluated. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-59060-8_59 | ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2017, PT II |
Keywords | Field | DocType |
Particle Swarm Optimization, PSO, ARPSO, CEC, Search space, Boundaries | Particle swarm optimization,Topology,Pattern recognition,Computer science,Algorithm,Artificial intelligence,Universe,Particle | Conference |
Volume | ISSN | Citations |
10246 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tomas Kadavy | 1 | 20 | 20.97 |
| Michal Pluhacek | 2 | 217 | 47.34 |
| Adam Viktorin | 3 | 29 | 16.76 |
| Roman Senkerik | 4 | 375 | 74.92 |