Abstract
A particle swarm optimization (PSO) system is one of the powerful systems for solving global optimization problems. The PSO algorithm can search an optimal value of a given evaluation function quickly compared with other proposed meta-heuristics algorithms. The conventional PSO system contains some random factors, therefore, the dynamics of the system can be regarded as stochastic dynamical systems. In order to analyze the dynamics rigorously, some papers pay attention to deterministic PSO systems which does not contain any stochastic factors. According to these results, the eigenvalues of the system impinge on the dynamics of the particles. Depending on the parameter, the searching ability of the deterministic PSO is decreased. In order to overcome this, we propose a canonical deterministic PSO which can control its eigenvalues easily, and can improve the searching ability. We confirmed relation between the eigenvalues and the searching ability of the optimal value from some numerical experiments.
| Translated title of the contribution | The Influence of Network Structure of Deterministic PSO Systems |
|---|---|
| Original language | Japanese |
| Pages (from-to) | 151 - 156 |
| Journal | 電子情報通信学会技術研究報告 |
| Volume | 110 |
| Issue number | 83(NC2010 1-28) |
| State | Published - 11 Jun 2010 |