Differential evolution for adaptive system of particle swarm optimization with genetic algorithm

Pham Ngoc Hieu, Hiroshi Hasegawa

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

A new strategy using Differential Evolution (DE) for Adaptive Plan System of Particle Swarm Optimization (PSO) with Genetic Algorithm (GA) called DE-PSO-APGA is proposed to solve a huge scale optimization problem, and to improve the convergence towards the optimal solution. This is an approach that combines the global search ability of GA and Adaptive plan (AP) for local search ability. The proposed strategy incorporates concepts from DE and PSO, updating particles not only by DE operators but also by mechanism of PSO for Adaptive System (AS). The DE-PSO-APGA is applied to several benchmark functions with multi-dimensions to evaluate its performance. We confirmed satisfactory performance through various benchmark tests.

本文言語English
ホスト出版物のタイトルIJCCI 2012 - Proceedings of the 4th International Joint Conference on Computational Intelligence
ページ259-264
ページ数6
出版ステータスPublished - 2012 12 1
イベント4th International Joint Conference on Computational Intelligence, IJCCI 2012 - Barcelona, Spain
継続期間: 2012 10 52012 10 7

出版物シリーズ

名前IJCCI 2012 - Proceedings of the 4th International Joint Conference on Computational Intelligence

Conference

Conference4th International Joint Conference on Computational Intelligence, IJCCI 2012
CountrySpain
CityBarcelona
Period12/10/512/10/7

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

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