Hierarchical heterogeneous particle swarm optimization

Xinpei Ma*, Hiroki Sayama

*この研究の対応する著者

研究成果: Conference contribution

抄録

Particle swarm optimization (PSO) has recently been modified to several versions. Heterogeneous PSO is a recent extension which includes behavioral heterogeneity of particles. Here we propose a further developed version that has hierarchical interaction patterns among heterogeneous particles, which we call hierarchical heterogeneous PSO (HHPSO). Two algorithm designs that have been developed and tested are multi-layer HHPSO (ml-HHPSO) and multi-group HHPSO (mg-HHPSO). The performances of these algorithms were measured on a set of benchmark functions and compared with standard PSO and heterogeneous PSO. The results showed that the performances of both HHPSO algorithms were significantly improved from standard PSO and heterogeneous PSO, with higher quality of optimal solutions and faster convergence speed.

本文言語English
ホスト出版物のタイトルArtificial Life 14 - Proceedings of the 14th International Conference on the Synthesis and Simulation of Living Systems, ALIFE 2014
編集者Hiroki Sayama, John Rieffel, Sebastian Risi, Rene Doursat, Hod Lipson
出版社MIT Press Journals
ページ629-630
ページ数2
ISBN(電子版)9780262326216
出版ステータスPublished - 2014
外部発表はい
イベント14th International Conference on the Synthesis and Simulation of Living Systems, ALIFE 2014 - Manhattan, United States
継続期間: 2014 7 302014 8 2

出版物シリーズ

名前Artificial Life 14 - Proceedings of the 14th International Conference on the Synthesis and Simulation of Living Systems, ALIFE 2014

Conference

Conference14th International Conference on the Synthesis and Simulation of Living Systems, ALIFE 2014
国/地域United States
CityManhattan
Period14/7/3014/8/2

ASJC Scopus subject areas

  • 生化学、遺伝学、分子生物学(全般)
  • 人工知能
  • モデリングとシミュレーション

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