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The Importance of Component-Wise Stochasticity in Particle Swarm Optimization

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Swarm Intelligence (ANTS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11172))

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Abstract

This paper illustrates the importance of independent, component-wise stochastic scaling values, from both a theoretical and empirical perspective. It is shown that a swarm employing scalar stochasticity is unable to express every point in the search space if the problem dimensionality is sufficiently large in comparison to the swarm size. The theoretical result is emphasized by an empirical experiment, comparing the performance of a scalar swarm on benchmarks with reachable and unreachable optima. It is shown that a swarm using scalar stochasticity performs significantly worse when the optimum is not in the span of its initial positions. Lastly, it is demonstrated that a scalar swarm performs significantly worse than a swarm with component-wise stochasticity on a large range of benchmark functions, even when the problem dimensionality allows the scalar swarm to reach the optima.

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Acknowledgments

This work is based on the research supported by the National Research Foundation (NRF) of South Africa (Grant Number 46712). The opinions, findings and conclusions or recommendations expressed in this article is that of the author(s) alone, and not that of the NRF. The NRF accepts no liability whatsoever in this regard.

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Authors and Affiliations

  1. Department of Computer Science, University of Pretoria, Pretoria, South Africa

    Elre T. Oldewage, Andries P. Engelbrecht & Christopher W. Cleghorn

  2. Council for Scientific and Industrial Research, Pretoria, South Africa

    Elre T. Oldewage

  3. Institute for Big Data and Data Science, Pretoria, South Africa

    Andries P. Engelbrecht

Authors
  1. Elre T. Oldewage
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  2. Andries P. Engelbrecht
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  3. Christopher W. Cleghorn
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Corresponding author

Correspondence to Elre T. Oldewage .

Editor information

Editors and Affiliations

  1. Université Libre de Bruxelles, Brussels, Belgium

    Marco Dorigo

  2. Université Libre de Bruxelles, Brussels, Belgium

    Mauro Birattari

  3. Artificial Intelligence Research Institute, Bellaterra, Spain

    Christian Blum

  4. University of Southern Denmark, Odense, Denmark

    Anders L. Christensen

  5. University of Sheffield, Sheffield, UK

    Andreagiovanni Reina

  6. National Research Council, Rome, Italy

    Vito Trianni

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Oldewage, E.T., Engelbrecht, A.P., Cleghorn, C.W. (2018). The Importance of Component-Wise Stochasticity in Particle Swarm Optimization. In: Dorigo, M., Birattari, M., Blum, C., Christensen, A., Reina, A., Trianni, V. (eds) Swarm Intelligence. ANTS 2018. Lecture Notes in Computer Science(), vol 11172. Springer, Cham. https://doi.org/10.1007/978-3-030-00533-7_21

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  • DOI: https://doi.org/10.1007/978-3-030-00533-7_21

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-00533-7

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