Improving particle swarm optimization with differentially perturbed velocity

Authors:
Swagatam Das;Amit Konar;Uday K. Chakraborty
Affiliations:
Jadavpur University, Kolkata, India;Jadavpur University, Kolkata, India;University of Missouri, St. Louis, MO
Venue:
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Year:
2005

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Abstract

This paper introduces a novel scheme of improving the performance of particle swarm optimization (PSO) by a vector differential operator borrowed from differential evolution (DE). Performance comparisons of the proposed method are provided against (a) the original DE, (b) the canonical PSO, and (c) three recent, high-performance PSO-variants. The new algorithm is shown to be statistically significantly better on a seven-function test suite for the following performance measures: solution quality, time to find the solution, frequency of finding the solution, and scalability.