HYBRID APPROACH FOR IMPROVED PARTICLE SWARM OPTIMIZATION USING ADAPTIVE PLAN SYSTEM WITH GENETIC ALGORITHM

Pham Ngoc Hieu, Hiroshi Hasegawa

Abstract

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.

References

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Paper Citation


in Harvard Style

Ngoc Hieu P. and Hasegawa H. (2011). HYBRID APPROACH FOR IMPROVED PARTICLE SWARM OPTIMIZATION USING ADAPTIVE PLAN SYSTEM WITH GENETIC ALGORITHM . In Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011) ISBN 978-989-8425-83-6, pages 267-272. DOI: 10.5220/0003626202670272


in Bibtex Style

@conference{ecta11,
author={Pham Ngoc Hieu and Hiroshi Hasegawa},
title={HYBRID APPROACH FOR IMPROVED PARTICLE SWARM OPTIMIZATION USING ADAPTIVE PLAN SYSTEM WITH GENETIC ALGORITHM},
booktitle={Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011)},
year={2011},
pages={267-272},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003626202670272},
isbn={978-989-8425-83-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2011)
TI - HYBRID APPROACH FOR IMPROVED PARTICLE SWARM OPTIMIZATION USING ADAPTIVE PLAN SYSTEM WITH GENETIC ALGORITHM
SN - 978-989-8425-83-6
AU - Ngoc Hieu P.
AU - Hasegawa H.
PY - 2011
SP - 267
EP - 272
DO - 10.5220/0003626202670272