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Floating boundary particle swarm optimization algorithm

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Abstract

A new modification to the particle swarm optimization (PSO) algorithm is proposed aiming to make the algorithm less sensitive to selection of the initial search domain. To achieve this goal, we release the boundaries of the search domain and enable each boundary to drift independently, guided by the number of collisions with particles involved in the optimization process. The gradual modification of the active search domain range enables us to prevent particles from revisiting less promising regions of the search domain and also to explore the areas located outside the initial search domain. With time, the search domain shrinks around a region holding a global extremum. This helps improve the quality of the final solution obtained. It also makes the algorithm less sensitive to initial choice of the search domain ranges. The effectiveness of the proposed Floating Boundary PSO (FBPSO) is demonstrated using a set of standard test functions. To control the performance of the algorithm, new parameters are introduced. Their optimal values are determined through numerical examples.

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Author notes

  1. Aleksey Y. Galan

    Present address: ATLAS Group, Labortório de Instrumentação e Física Experimental de Partículas, Lisbon, Portugal

  2. Artem V. Boriskin

    Present address: Institut d’Electronique et de Télécommunications de Rennes (IETR), UMR CNRS 6164, Université de Rennes 1, Rennes, France

Authors and Affiliations

  1. Institute of Radiophysics and Electronics of the National Academy of Sciences of Ukraine (IRE NASU), Kharkov, Ukraine

    Aleksey Y. Galan & Artem V. Boriskin

  2. Institut d’Electronique et de Télécommunications de Rennes (IETR), UMR CNRS 6164, Université de Rennes 1, Rennes, France

    Ronan Sauleau

Authors
  1. Aleksey Y. Galan
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  2. Ronan Sauleau
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  3. Artem V. Boriskin
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Corresponding author

Correspondence to Artem V. Boriskin.

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Galan, A.Y., Sauleau, R. & Boriskin, A.V. Floating boundary particle swarm optimization algorithm. Optim Lett 7, 1261–1280 (2013). https://doi.org/10.1007/s11590-012-0502-8

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  • DOI: https://doi.org/10.1007/s11590-012-0502-8

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