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Pre-scheduled Colony Size Variation in Dynamic Environments

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Applications of Evolutionary Computation (EvoApplications 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10200))

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Abstract

The performance of the \(\mathcal {MAX}\)-\(\mathcal {MIN}\) ant system (\(\mathcal {MM}\)AS) in dynamic optimization problems (DOPs) is sensitive to the colony size. In particular, a large colony size may waste computational resources whereas a small colony size may restrict the searching capabilities of the algorithm. There is a trade off in the behaviour of the algorithm between the early and later stages of the optimization process. A smaller colony size leads to better performance on shorter runs whereas a larger colony size leads to better performance on longer runs. In this paper, pre-scheduling of varying the colony size of \(\mathcal {MM}\)AS is investigated in dynamic environments.

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Acknowledgement

This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of U.K. under Grant EP/K001310/1.

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Authors and Affiliations

  1. School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham, NG11 8NS, UK

    Michalis Mavrovouniotis

  2. Department of Informatics, University of Leicester, University Road, Leicester, LE1 7RH, UK

    Anastasia Ioannou

  3. Centre for Computational Intelligence (CCI), School of Computer Science and Informatics, De Montfort University, The Gateway, Leicester, LE1 9BH, UK

    Shengxiang Yang

Authors
  1. Michalis Mavrovouniotis
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  2. Anastasia Ioannou
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  3. Shengxiang Yang
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Correspondence to Michalis Mavrovouniotis .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Giovanni Squillero

  2. Edinburgh Napier University, Edinburgh, United Kingdom

    Kevin Sim

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Mavrovouniotis, M., Ioannou, A., Yang, S. (2017). Pre-scheduled Colony Size Variation in Dynamic Environments. In: Squillero, G., Sim, K. (eds) Applications of Evolutionary Computation. EvoApplications 2017. Lecture Notes in Computer Science(), vol 10200. Springer, Cham. https://doi.org/10.1007/978-3-319-55792-2_9

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  • DOI: https://doi.org/10.1007/978-3-319-55792-2_9

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-55792-2

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