Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 23-30 |
| Number of pages | 8 |
| Journal | Electronics and Communications in Japan |
| Volume | 91 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2008 Feb |
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Keywords
- Dissipative dynamical system
- Global optimization
- Particle swarm optimization
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Computer Networks and Communications
- Physics and Astronomy(all)
- Signal Processing
- Applied Mathematics
Cite this
Proposal of particle swarm optimization methods with nonlinear dissipative term. / Murata, Hideki; Yasuda, Keiichiro; Aiyoshi, Eitaro.
In: Electronics and Communications in Japan, Vol. 91, No. 2, 02.2008, p. 23-30.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Proposal of particle swarm optimization methods with nonlinear dissipative term
AU - Murata, Hideki
AU - Yasuda, Keiichiro
AU - Aiyoshi, Eitaro
PY - 2008/2
Y1 - 2008/2
N2 - 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.
AB - 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.
KW - Dissipative dynamical system
KW - Global optimization
KW - Particle swarm optimization
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UR - http://www.scopus.com/inward/citedby.url?scp=65249112346&partnerID=8YFLogxK
U2 - 10.1002/ecj.10028
DO - 10.1002/ecj.10028
M3 - Article
VL - 91
SP - 23
EP - 30
JO - Electronics and Communications in Japan
JF - Electronics and Communications in Japan
SN - 1942-9533
IS - 2
ER -