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The Generalized Particle Swarm Optimization Algorithm: Idea, Analysis, and Engineering Applications
Abstract
A generalization of the popular and widely used Particle Swarm Optimization (PSO) algorithm is presented in this chapter. This novel optimizer, named Generalized PSO (GPSO), is inspired by linear control theory. It enables direct control over the key aspects of particle dynamics during the optimization process, overcoming some typical flaws of classical PSO. The basic idea of this algorithm with its detailed theoretical and empirical analysis is presented, and parameter-tuning schemes are proposed. GPSO is also compared to the classical PSO and Genetic Algorithm (GA) on a set of benchmark problems. The results clearly demonstrate the effectiveness of the proposed algorithm. Finally, two practical engineering applications of the GPSO algorithm are described, in the area of electrical machines fault detection and classification, and in optimal control of water distribution systems.
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