Abstract

This work introduces a novel technique for dynamic particle swarm optimization (DPSO) using adaptive critic designs. The adaptation between global and local search in an optimization algorithm is critical for optimization problems especially in a dynamically changing environment or process over time. The inertia weight in particle swarm optimization (PSO) is dynamically adjusted in this paper in order to provide a nonlinear search capability for the PSO algorithm. Results on benchmark functions in the literature are provided.

Meeting Name

2004 IEEE International Symposium on Intelligent Control, 2004

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Adaptive Critics Design; Dynamic Particle Swarm Optimization; Global Search; Local Search; Optimisation; Search Problems

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2004 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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