Differential Evolution for Adaptive System of Particle Swarm Optimization with Genetic Algorithm

Pham Ngoc Hieu, Hiroshi Hasegawa

2012

Abstract

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.

References

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Paper Citation

in Harvard Style

Ngoc Hieu P. and Hasegawa H. (2012). Differential Evolution for Adaptive System of Particle Swarm Optimization with Genetic Algorithm . In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 259-264. DOI: 10.5220/0004107202590264

in Bibtex Style

@conference{ecta12,
author={Pham Ngoc Hieu and Hiroshi Hasegawa},
title={Differential Evolution for Adaptive System of Particle Swarm Optimization with Genetic Algorithm},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012)},
year={2012},
pages={259-264},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004107202590264},
isbn={978-989-8565-33-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012)
TI - Differential Evolution for Adaptive System of Particle Swarm Optimization with Genetic Algorithm
SN - 978-989-8565-33-4
AU - Ngoc Hieu P.
AU - Hasegawa H.
PY - 2012
SP - 259
EP - 264
DO - 10.5220/0004107202590264