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A Memetic Cooperative Co-evolution Model for Large Scale Continuous Optimization

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Artificial Life and Computational Intelligence (ACALCI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10142))

Abstract

Cooperative co-evolution (CC) is a framework that can be used to ‘scale up’ EAs to solve high dimensional optimization problems. This approach employs a divide and conquer strategy, which decomposes a high dimensional problem into sub-components that are optimized separately. However, the traditional CC framework typically employs only one EA to solve all the sub-components, which may be ineffective. In this paper, we propose a new memetic cooperative co-evolution (MCC) framework which divides a high dimensional problem into several separable and non-separable sub-components based on the underlying structure of variable interactions. Then, different local search methods are employed to enhance the search of an EA to solve the separable and non-separable sub-components. The proposed MCC model was evaluated on two benchmark sets with 35 benchmark problems. The experimental results confirmed the effectiveness of our proposed model, when compared against two traditional CC algorithms and a state-of-the-art memetic algorithm.

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia

    Yuan Sun

  2. Department of Computing and Information Systems, The University of Melbourne, Parkville, Victoria, 3010, Australia

    Michael Kirley

  3. Research School of Engineering, The Australian National University, Canberra, Australian Capital Territory, 2601, Australia

    Saman K. Halgamuge

Authors
  1. Yuan Sun
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  2. Michael Kirley
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  3. Saman K. Halgamuge
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Corresponding author

Correspondence to Yuan Sun .

Editor information

Editors and Affiliations

  1. The University of Adelaide, Adelaide, South Australia, Australia

    Markus Wagner

  2. RMIT University, Melbourne, Victoria, Australia

    Xiaodong Li

  3. Swinburne University, Melbourne, Victoria, Australia

    Tim Hendtlass

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Sun, Y., Kirley, M., Halgamuge, S.K. (2017). A Memetic Cooperative Co-evolution Model for Large Scale Continuous Optimization. In: Wagner, M., Li, X., Hendtlass, T. (eds) Artificial Life and Computational Intelligence. ACALCI 2017. Lecture Notes in Computer Science(), vol 10142. Springer, Cham. https://doi.org/10.1007/978-3-319-51691-2_25

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  • DOI: https://doi.org/10.1007/978-3-319-51691-2_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51690-5

  • Online ISBN: 978-3-319-51691-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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