Proceedings of the Korea Society for Industrial Systems Conference (한국산업정보학회:학술대회논문집)

Korea Society of Industrial Information Systems (한국산업정보학회)
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A Hybridization of Adaptive Genetic Algorithm and Particle Swarm Optimization for Numerical Optimization Functions

  • Yun, Young-Su (Division of Business Administration, Chosun University) ;
  • Gen, Mitsuo (School of Information, Production & Systems, Waseda University)
  • Published : 2008.10.31
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Abstract

Heuristic optimization using hybrid algorithms have provided a robust and efficient approach for solving many optimization problems. In this paper, a new hybrid algorithm using adaptive genetic algorithm (aGA) and particle swarm optimization (PSO) is proposed. The proposed hybrid algorithm is applied to solve numerical optimization functions. The results are compared with those of GA and other conventional PSOs. Finally, the proposed hybrid algorithm outperforms others.

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