Name
Abstract | ||
|---|---|---|
This paper proposes a Repulsive Adaptive PSO (RAPSO) variant that adaptively optimizes the velocity weights of every particle at every iteration. RAPSO optimizes the velocity weights during every outer PSO iteration, and optimizes the solution of the problem in an inner PSO iteration. We compare RAPSO to Global Best PSO (GBPSO) on nine benchmark problems, and the results show that RAPSO out-performs GBPSO on difficult optimization problems. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2464576.2464584 | GECCO (Companion) |
Keywords | Field | DocType |
difficult optimization problem,adaptively optimizes,velocity weight,rapso out-performs gbpso,outer pso iteration,global best pso,benchmark problem,inner pso iteration,repulsive adaptive pso,adaptive particle swarm optimization,evolutionary computation | Particle swarm optimization,Mathematical optimization,Computer science,Algorithm,Evolutionary computation,Artificial intelligence,Optimization problem,Machine learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Simone A Ludwig | 1 | 1309 | 179.41 |