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Social Strategy of Particles in Optimization Problems

  • Bożena BorowskaEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 991)

Abstract

The article presents a particle swarm optimization algorithm (SoPSO) in which a novel effective acceleration coefficient has been proposed. In the presented approach, the proposed acceleration coefficient is a nonlinear function that depends on the performance of the algorithm and is affected by a number of iterations. This strategy allows to more precisely specify the search direction and better control velocity of the algorithm according to which it travels in the search space to discover the best, optimal solution of the considered problem. The presented strategy was examined on the collection of benchmark functions described in the literature. The test results were compared with those achieved by the improved IPSO algorithm and the standard PSO (SPSO).

Keywords

Swarm intelligence Socials strategy Particle swarm optimization Optimization 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Information Technology, Lodz University of TechnologyLodzPoland

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