Name
Abstract | ||
|---|---|---|
The PSO (Particle Swarm Optimization) metaheuristics, originally defined for solving single-objective problems, has been applied to multi-objective problems with very good results. In its initial conception, the algorithm has a fixed-size population. In this paper, a new variation of this metaheuristics, called VarMOPSO (Variable Multi-Objective Particle Swarm Optimization), characterized by a variable-sized population, is proposed. To this end, the concepts of age and neighborhood are incorporated to be able to modify the size of the population for the different generations. This algorithm was compared with the version that uses fixed-size populations, as well as with other metaheuristics, all of them representative of the state of the art in multi-objective optimization. In all cases, three widely used metrics were considered as quality indicators for Pareto front. The results obtained were satisfactory. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-16952-6_7 | IBERAMIA |
Keywords | Field | DocType |
pareto front,population size,evolutionary computing,swarm intelligence,multi objective optimization,objective function | Ant colony optimization algorithms,Particle swarm optimization,Mathematical optimization,Parallel metaheuristic,Meta-optimization,Multi-swarm optimization,Multi-objective optimization,Imperialist competitive algorithm,Mathematics,Metaheuristic | Conference |
Volume | ISSN | ISBN |
6433 | 0302-9743 | 3-642-16951-1 |
Citations | PageRank | References |
2 | 0.47 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Javier H. López | 1 | 2 | 0.81 |
| Laura Lanzarini | 2 | 21 | 8.94 |
| Armando Giusti | 3 | 71 | 21.17 |