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Dynamic Inertia Weight in Particle Swarm Optimization

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Advances in Intelligent Systems and Computing II (CSIT 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 689))

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Abstract

This paper proposes a particle swarm optimization method with a novel strategy for inertia weight. Instead of a commonly used linear inertia weight, a nonlinear, dynamic changing inertia weight is applied. The new presented weight is a function of the worst and the best fitness of individuals of a population. In order to investigate the effectiveness of the proposed strategy tests on a set of benchmark function were conducted. The results were compared with those obtained through the LDW-PSO method, EWPSO and the RNW-PSO methods.

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Authors and Affiliations

  1. Institute of Information Technology, Lodz University of Technology, Wólczańska 215, 90-924, Łodź, Poland

    Bożena Borowska

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  1. Bożena Borowska
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Correspondence to Bożena Borowska .

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Editors and Affiliations

  1. Lviv Polytechnic National University, Lviv, Ukraine

    Natalia Shakhovska

  2. IRTC ITS NASU, Kiev, Ukraine

    Volodymyr Stepashko

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Borowska, B. (2018). Dynamic Inertia Weight in Particle Swarm Optimization. In: Shakhovska, N., Stepashko, V. (eds) Advances in Intelligent Systems and Computing II. CSIT 2017. Advances in Intelligent Systems and Computing, vol 689. Springer, Cham. https://doi.org/10.1007/978-3-319-70581-1_6

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  • DOI: https://doi.org/10.1007/978-3-319-70581-1_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70580-4

  • Online ISBN: 978-3-319-70581-1

  • eBook Packages: EngineeringEngineering (R0)

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