Proposal of particle swarm optimization methods with nonlinear dissipative term

Hideki Murata, Keiichiro Yasuda, Eitaro Aiyoshi

研究成果: Article査読

1 被引用数 (Scopus)


Optimization methods based on metaheuristics are proposed as a class of global optimization methods, by which the global minimum can be obtained without being trapped in local minima. Particle swarm optimization (PSO), which is one of these methods, is known for its high searching ability and easy implementation. However, it might be difficult to find the global optimum for optimization problems with a number of decision variables and multiple local optima. In this paper, we propose three types of new PSO methods to overcome this difficulty. One is a model with nonlinear dissipative term introduced by Fujita and colleagues [4] to prohibit the search point's velocity from being zero. The others are models with the nonlinear dissipative term with the pbest or the gbest information to disturb the search around them.

ジャーナルElectronics and Communications in Japan
出版ステータスPublished - 2008 2月 1

ASJC Scopus subject areas

  • 信号処理
  • 物理学および天文学(全般)
  • コンピュータ ネットワークおよび通信
  • 電子工学および電気工学
  • 応用数学


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