Abstract
To balance exploration and exploitation searches in order to prevent premature convergences in Particle Swarm Optimization (PSO) algorithms, an improved Quantum-based PSO (QPSO) algorithm is proposed with an ultimate goal of preserving the simplicities of available QPSOs. The improvements include the design of diversification and intensification phases, searching mechanisms and a strategy to shift away from the worst solutions. The proposed QPSO are compared to available optimizers on two case studies to showcase its merits.
| Original language | English |
|---|---|
| Article number | 6514656 |
| Pages (from-to) | 2069-2072 |
| Number of pages | 4 |
| Journal | IEEE Transactions on Magnetics |
| Volume | 49 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 22 May 2013 |
Keywords
- Evolutionary algorithm
- inverse problem
- optimal design
- particle swarm optimization
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Electronic, Optical and Magnetic Materials
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