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Advances in Nature and Biologically Inspired Computing pp 393–403Cite as

Updating the Global Best and Archive Solutions of the Dynamic Vector-Evaluated PSO Algorithm Using \(\epsilon \)-dominance

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 419))

Abstract

Dynamic multi-objective optimisation problems have more than one objective, at least two objectives that are in conflict with one another and at least one objective that changes over time. These kinds of problems do not have a single optimum due to the conflict between the objectives. Therefore, a new approach is required to determine the quality of a solution. Traditionally in multi-objective optimisation (MOO) Pareto-dominance have been used to compare the quality of two solutions. However, in order to increase the speed of convergence and the diversity of the found solutions, \(\epsilon \)-dominance has been proposed. This study investigates the effect of using \(\epsilon \)-dominance for two aspects of the dynamic vector evaluated particle swarm optimisation (DVEPSO) algorithm, namely: updating the global best and managing the archive solutions. The results indicate that applying \(\epsilon \)-dominance instead of Pareto-dominance to either both of these aspects of the algorithm, or only to the global best update, does improve the performance of DVEPSO.

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Authors and Affiliations

  1. Department of Computer Science, University of Pretoria, Hatfield, South Afria

    Mardé Helbig

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  1. Mardé Helbig
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Correspondence to Mardé Helbig .

Editor information

Editors and Affiliations

  1. School of Mathematics, Statistics and CS, University of KwaZulu-Natal, Pietermaritzburg, South Africa

    Nelishia Pillay

  2. Sch of IT, Dept of CS, University of Pretoria, Pretoria, South Africa

    Andries P. Engelbrecht

  3. Sci N/w for Innova and Research Exc, Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  4. Department of Computing Sciences,, Nelson Mandela Metropolitan University, Port Elizabeth, South Africa

    Mathys C. du Plessis

  5. Faculty of Electrical Engineering and, Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Václav Snášel

  6. Fakulti Teknologi Maklumat dan Komunikas, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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Helbig, M. (2016). Updating the Global Best and Archive Solutions of the Dynamic Vector-Evaluated PSO Algorithm Using \(\epsilon \)-dominance. In: Pillay, N., Engelbrecht, A., Abraham, A., du Plessis, M., Snášel, V., Muda, A. (eds) Advances in Nature and Biologically Inspired Computing. Advances in Intelligent Systems and Computing, vol 419. Springer, Cham. https://doi.org/10.1007/978-3-319-27400-3_35

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  • DOI: https://doi.org/10.1007/978-3-319-27400-3_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27399-0

  • Online ISBN: 978-3-319-27400-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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