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.
G. K. Venayagamoorthy and S. Doctor, "Improving the Performance of Particle Swarm Optimization Using Adaptive Critics Designs," Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005, Institute of Electrical and Electronics Engineers (IEEE), Jan 2005.
The definitive version is available at https://doi.org/10.1109/SIS.2005.1501649
2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005
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
Article - Conference proceedings
© 2005 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Jan 2005