Abstract

Swarm intelligence algorithms are based on natural behaviors. Particle swarm optimization (PSO) is a stochastic search and optimization tool. Changes in the PSO parameters, namely the inertia weight and the cognitive and social acceleration constants, affect the performance of the search process. This paper presents a novel method to dynamically change the values of these parameters during the search. Adaptive critic design (ACD) has been applied for dynamically changing the values of the PSO parameters.

Meeting Name

2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Adaptive Critics Design; Particle Swarm Optimisation; Particle Swarm Optimization Algorithm; Search Problems; Stochastic Processes; Stochastic Search Tool; Swarm Intelligence Algorithm

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2005 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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