Deterministic Particle Swarm Optimizer with the Convergence and Divergence Dynamics

Tomoyuki SASAKI  Hidehiro NAKANO  Arata MIYAUCHI  Akira TAGUCHI  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E100-A    No.5    pp.1244-1247
Publication Date: 2017/05/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E100.A.1244
Type of Manuscript: LETTER
Category: Nonlinear Problems
particle swarm optimizer,  deterministic particle swarm optimizer,  piecewise-linear system,  piecewise-linear particle swarm optimizer,  

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In this paper, we propose a new paradigm of deterministic PSO, named piecewise-linear particle swarm optimizer (PPSO). In PPSO, each particle has two search dynamics, a convergence mode and a divergence mode. The trajectory of each particle is switched between the two dynamics and is controlled by parameters. We analyze convergence condition of each particle and investigate parameter conditions to allow particles to converge to an equilibrium point through numerical experiments. We further compare solving performances of PPSO. As a result, we report here that the solving performances of PPSO are substantially the same as or superior to those of PSO.