繰り返し型探索指針による Particle Swarm Optimization の改良 Improvement of Particle Swarm Optimization Based on the Repetitive Search Guideline
Particle Swarm Optimization (PSO), which has attracted a great deal of attention as a global optimization method in recent years, has a drawback in that its continuous search based on its excellent dynamic characteristics can not be executed stably until the end of computation due to its much strong convergence trend. In this paper, we propose "Repetitive Search Guideline" which differs from a common guideline in the improved methods which have ever been proposed and by which the continuous search of PSO is achieved without lack of PSO's excellent dynamic characteristics due to the repetitive search in a promise area where objective function value is expected to be small. We consider four improved methods based on the proposed guideline, and then, their effectiveness are confirmed through applications to 100 variables multi-peaked benchmark problems.
- 電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society
電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society 128(7), 1143-1153, 2008-07-01
The Institute of Electrical Engineers of Japan