Adaptive system of swarm intelligent with Genetic Algorithm for global optimization

Hieu Pham, Hiroshi Hasegawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Pages171-176
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012 - Seoul
Duration: 2012 Oct 142012 Oct 17

Other

Other2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012
CitySeoul
Period12/10/1412/10/17

Fingerprint

Adaptive systems
Global optimization
Genetic algorithms
Particle swarm optimization (PSO)
Genes
Mathematical operators

Keywords

  • Adaptive System
  • Genetic Algorithm
  • Multi-peak problems
  • Particle Swarm Optimization

ASJC Scopus subject areas

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

Cite this

Pham, H., & Hasegawa, H. (2012). Adaptive system of swarm intelligent with Genetic Algorithm for global optimization. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics (pp. 171-176). [6377695] https://doi.org/10.1109/ICSMC.2012.6377695

Adaptive system of swarm intelligent with Genetic Algorithm for global optimization. / Pham, Hieu; Hasegawa, Hiroshi.

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. 2012. p. 171-176 6377695.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Pham, H & Hasegawa, H 2012, Adaptive system of swarm intelligent with Genetic Algorithm for global optimization. in Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics., 6377695, pp. 171-176, 2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012, Seoul, 12/10/14. https://doi.org/10.1109/ICSMC.2012.6377695
Pham H, Hasegawa H. Adaptive system of swarm intelligent with Genetic Algorithm for global optimization. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. 2012. p. 171-176. 6377695 https://doi.org/10.1109/ICSMC.2012.6377695
Pham, Hieu ; Hasegawa, Hiroshi. / Adaptive system of swarm intelligent with Genetic Algorithm for global optimization. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. 2012. pp. 171-176
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