Adaptive system of swarm intelligent with Genetic Algorithm for global optimization

Hieu Pham, Hiroshi Hasegawa

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

A new strategy of Adaptive Plan System with Genetic Algorithm (APGA) is proposed to reduce a large amount of calculation cost and to improve stability in convergence to an optimal solution for multi-peak optimization problems with multi-dimensions. This is an approach that combines the global search ability of Genetic Algorithm (GA) and the local search ability of Adaptive Plan (AP). The APGA differs from GAs in handling design variable vectors (DVs). GAs generally encode DVs into genes and handle them through GA operators. However, the APGA encodes control variable vectors (CVs) of AP, which searches for local optimum, into its genes. CVs determine the global behavior of AP, and DVs are handled by AP in the optimization process of APGA. In this paper, we introduce a new approach for Adaptive Plan System of swarm intelligent using Particle Swarm Optimization (PSO) with Genetic Algorithm (PSO-APGA) to solve a huge scale optimization problem, and to improve the convergence towards the optimal solution. The 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Proceedings 2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012
ページ171-176
ページ数6
DOI
出版ステータスPublished - 2012 12 1
イベント2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012 - Seoul, Korea, Republic of
継続期間: 2012 10 142012 10 17

出版物シリーズ

名前Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN(印刷版)1062-922X

Conference

Conference2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012
CountryKorea, Republic of
CitySeoul
Period12/10/1412/10/17

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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