The global optimization with the PSO coupling type discrete gradient chaos model

Takashi Okamoto, Eitaro Aiyoshi

Research output: Contribution to journalArticlepeer-review


In this paper, we propose a new multi-agent discrete gradient chaos model using a coupling structure which PSO has. Concretely, firstly, we introduce a multi-agent type optimization model whose agents search autonomously with the discrete gradient chaos model which is the simplest dynamical global search model, and they are coupled by convective coupling. Convective coupling in this model is used to aim at a overcoming of emergence of boundary crisis which is a problem of original discrete gradient chaos model. Secondary, we introduce PSO coupling structure, where population drifts to the gbest and the pbest, into discrete gradient chaos model. Then, we propose "PSO coupling type discrete gradient chaos model" with the search strategy based on objective function's value. In this paper, our proposal models are applied to several benchmark problems. The results show that our proposed models have better global optimization ability than original discrete gradient chaos model and PSO model.

Original languageEnglish
Pages (from-to)857-864
Number of pages8
JournalIEEJ Transactions on Electronics, Information and Systems
Issue number7
Publication statusPublished - 2006


  • Chaos
  • Coupling model
  • Global optimization
  • Gradient system
  • Multi-agent system model
  • Particle swarm optimization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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