Particle Convergence Time in the Deterministic Model of PSO

• Published in: Computational Intelligence Vol. 669; pp. 175 - 194
• Main Authors: Trojanowski, Krzysztof, Kulpa, Tomasz
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2016; Springer International Publishing
• Series: Studies in Computational Intelligence
• ISBN: 3319485040; 9783319485041
• ISSN: 1860-949X; 1860-9503; 1860-9503
• DOI: 10.1007/978-3-319-48506-5_10

A property of particles in Particle Swarm Optimization (PSO), namely, particle convergence time (pct) is a subject of theoretical and experimental analysis. For the model of PSO with inertia weight a new measure for evaluation of pct is proposed. The measure evaluates number of steps necessary for a particle to obtain a stable state defined with any precision. For this measure an upper bound formula of pct is derived and its properties are studied. Four main types of particle behaviour characteristics are selected and discussed. In the experimental part of the research effectiveness of swarms with different characteristics of their members are verified. A new type of swarm control improving efficiency of a swarm in escaping traps of local optima is proposed and experimentally verified.