Premium
Global optimization with the PSO coupling‐type discrete gradient chaos model
Author(s) -
Okamoto Takashi,
Aiyoshi Eitaro
Publication year - 2008
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/eej.20563
Subject(s) - coupling (piping) , benchmark (surveying) , chaos (operating system) , particle swarm optimization , computer science , type (biology) , mathematical optimization , mathematics , engineering , geology , mechanical engineering , computer security , geodesy , paleontology
In this paper, we propose a new multiagent discrete gradient chaos model using a coupling structure which PSO has. Concretely, first, we introduce a multiagent‐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 overcoming of emergence of boundary crisis which is a problem of the original discrete gradient chaos model. Second, 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 proposed models are applied to several benchmark problems. The results show that our proposed models have better global optimization ability than the original discrete gradient chaos model and PSO model. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 165(4): 67–75, 2008; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20563