Basic study on particle swarm optimization with hierarchical structure for constrained optimization problems

  • Authors:

  • Kazuki Komori;Kazuhiro Homma;Tadashi Tsubone

  • Affiliations:

  • Nagaoka University of Technology, Nagaoka, Niigata, Japan;Information Technology Business Development Department, GaiaX Co. Ltd., Shinagawa-ku, Tokyo, Japan;Nagaoka University of Technology, Nagaoka, Niigata, Japan

  • Venue:
  • ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
  • Year:
  • 2012

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Abstract

In this work, we consider Particle Swarm Optimization (abbr. PSO) with hierarchical structures in order to solve some constrained optimization problems. The PSO with hierarchical structures has two layers. The lower layer is used to satisfy the constraint conditions and the upper layer is used to optimize the objective function. Due to these layers and the mutual function, the proposed method can be applied to constrained optimization problems which problems cannot be solved by the basic PSO. In this paper, we apply this procedure to some constrained optimization problems and evaluate its performance.