Name
Abstract | ||
|---|---|---|
The vector evaluated particle swarm optimization (VEPSO) algorithm is a cooperative, multi-swarm algorithm. Each sub-swarm optimizes only a single objective of a multi-objective problem (MOP), and implements a knowledge transfer strategy (KTS) to share optimal positions of the different objectives among the sub-swarms, guiding the particles to different regions of the Pareto front. This paper shows that the stagnation problem that occurs in VEPSO can be addressed by using a different KTS. A comparison is made between the ring-based and random knowledge transfer strategies. Experimental results show that the random knowledge transfer strategy suffers less from stagnation than the ring-based KTS, making it the preferred KTS to use. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SIS.2013.6615173 | 2013 IEEE SYMPOSIUM ON SWARM INTELLIGENCE (SIS) |
Keywords | Field | DocType |
Particle swarm optimization, Vector evaluated particle swarm optimization, Multi-objective optimization, Knowledge transfer strategies, Swarm speciation | Particle swarm optimization,Mathematical optimization,Knowledge transfer,Multi-objective optimization,Multi-swarm optimization,Single objective,Mathematics,Metaheuristic | Conference |
Citations | PageRank | References |
4 | 0.43 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wiehann Matthysen | 1 | 4 | 0.43 |
| Andries P. Engelbrecht | 2 | 660 | 61.64 |
| Katherine Malan | 3 | 162 | 12.77 |