New evolutionary algorithm based on particle swarm optimization and adaptive plan system with genetic algorithm

Pham Ngoc Hieu, Hiroshi Hasegawa

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

To reduce a large amount of calculation cost and to improve the convergence to the optimal solution for multi-peak optimization problems with multidimensions, we purpose a new method of Adaptive plan system with Genetic Algorithm (APGA). This is an approach for improving Particle Swarm Optimization (PSO) using APGA. The new strategy based on PSO operator and APGA (PSO-APGA) to improve the convergence towards the optimal solution. The PSOAPGA is applied to some benchmark functions with 20 dimensions to evaluate its performance.

Original languageEnglish
Pages249-254
Number of pages6
Publication statusPublished - 2011 Jan 1
Event10th International Conference on Modeling and Applied Simulation, MAS 2011, Held at the International Mediterranean and Latin American Modeling Multiconference, I3M 2011 - Rome, Italy
Duration: 2011 Sep 122011 Sep 14

Conference

Conference10th International Conference on Modeling and Applied Simulation, MAS 2011, Held at the International Mediterranean and Latin American Modeling Multiconference, I3M 2011
CountryItaly
CityRome
Period11/9/1211/9/14

Keywords

  • Adaptive system
  • Genetic algorithm
  • Multi-peak problems
  • Particle swarm optimization

ASJC Scopus subject areas

  • Modelling and Simulation

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    Hieu, P. N., & Hasegawa, H. (2011). New evolutionary algorithm based on particle swarm optimization and adaptive plan system with genetic algorithm. 249-254. Paper presented at 10th International Conference on Modeling and Applied Simulation, MAS 2011, Held at the International Mediterranean and Latin American Modeling Multiconference, I3M 2011, Rome, Italy.