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PSO–FWA: A New Hybrid Algorithm for Solving Nonlinear Equation Systems

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Computational Science and Its Applications – ICCSA 2023 Workshops (ICCSA 2023)

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Abstract

Nature-inspired optimization algorithms have been proposed for solving hard optimization problems, including the optimization-based solution of difficult systems of nonlinear equations. While there is no perfect optimization algorithm, the hybridization of such metaheuristic optimization algorithms has produced positive results by enhancing their capabilities and reducing their weaknesses. This paper presents a novel hybridization of Particle Swarm Optimization and the Fireworks Algorithm for solving nonlinear equation systems. The experimental results obtained indicate that the proposed hybrid algorithm outperforms both Particle Swarm Optimization and the Fireworks Algorithm, as well as a previously developed hybridization of these algorithms.

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Author information

Authors and Affiliations

  1. Postgraduate Program in Informatics Engineering, University of Madeira, Funchal, Madeira Is., Portugal

    Sérgio Ribeiro

  2. Faculty of Exact Sciences and Engineering, University of Madeira, 9020-105, Funchal, Madeira Is., Portugal

    Luiz Guerreiro Lopes

Authors
  1. Sérgio Ribeiro
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  2. Luiz Guerreiro Lopes
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Corresponding author

Correspondence to Sérgio Ribeiro .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Basilicata, Potenza, Italy

    Francesco Scorza

  6. University of Massachusetts Medical School, Worcester, MA, USA

    Yeliz Karaca

  7. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

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Ribeiro, S., Lopes, L.G. (2023). PSO–FWA: A New Hybrid Algorithm for Solving Nonlinear Equation Systems. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2023 Workshops. ICCSA 2023. Lecture Notes in Computer Science, vol 14112. Springer, Cham. https://doi.org/10.1007/978-3-031-37129-5_5

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  • DOI: https://doi.org/10.1007/978-3-031-37129-5_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-37128-8

  • Online ISBN: 978-3-031-37129-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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