Hybrid approach for improved particle swarm optimization using Adaptive plan system with genetic algorithm

Pham Ngoc Hieu, Hiroshi Hasegawa

研究成果: Conference contribution

抄録

To reduce a large amount of calculation cost and to improve the convergence to the optimal solution for multi-peak optimization problems with multi-dimensions, we purpose a new method of Adaptive plan system with Genetic Algorithm (APGA). This is an approach for Improved Particle Swarm Optimization (PSO) using APGA. The hybrid strategy using APGA is introduced into PSO operator (H-PSOGA) to improve the convergence towards the optimal solution. The H-PSOGA is applied to some benchmark functions with 20 dimensions to evaluate its performance.

本文言語English
ホスト出版物のタイトルECTA 2011 FCTA 2011 - Proceedings of the International Conference on Evolutionary Computation Theory and Applications and International Conference on Fuzzy Computation Theory and Applications
ページ267-272
ページ数6
出版ステータスPublished - 2011 12 1
イベントInternational Conference on Evolutionary Computation Theory and Applications, ECTA 2011 and International Conference on Fuzzy Computation Theory and Applications, FCTA 2011 - Paris, France
継続期間: 2011 10 242011 10 26

出版物シリーズ

名前ECTA 2011 FCTA 2011 - Proceedings of the International Conference on Evolutionary Computation Theory and Applications and International Conference on Fuzzy Computation Theory and Applications

Conference

ConferenceInternational Conference on Evolutionary Computation Theory and Applications, ECTA 2011 and International Conference on Fuzzy Computation Theory and Applications, FCTA 2011
CountryFrance
CityParis
Period11/10/2411/10/26

ASJC Scopus subject areas

  • Applied Mathematics

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