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Constructive cooperative coevolution for large-scale global optimisation

Author

Listed:
  • Emile Glorieux

    (University West)

  • Bo Svensson

    (University West)

  • Fredrik Danielsson

    (University West)

  • Bengt Lennartson

    (Chalmers University of Technology)

Abstract

This paper presents the Constructive Cooperative Coevolutionary ( $$\mathrm {C}^3$$ C 3 ) algorithm, applied to continuous large-scale global optimisation problems. The novelty of $$\mathrm {C}^3$$ C 3 is that it utilises a multi-start architecture and incorporates the Cooperative Coevolutionary algorithm. The considered optimisation problem is decomposed into subproblems. An embedded optimisation algorithm optimises the subproblems separately while exchanging information to co-adapt the solutions for the subproblems. Further, $$\mathrm {C}^3$$ C 3 includes a novel constructive heuristic that generates different feasible solutions for the entire problem and thereby expedites the search. In this work, two different versions of $$\mathrm {C}^3$$ C 3 are evaluated on high-dimensional benchmark problems, including the CEC’2013 test suite for large-scale global optimisation. $$\mathrm {C}^3$$ C 3 is compared with several state-of-the-art algorithms, which shows that $$\mathrm {C}^3$$ C 3 is among the most competitive algorithms. $$\mathrm {C}^3$$ C 3 outperforms the other algorithms for most partially separable functions and overlapping functions. This shows that $$\mathrm {C}^3$$ C 3 is an effective algorithm for large-scale global optimisation. This paper demonstrates the enhanced performance by using constructive heuristics for generating initial feasible solutions for Cooperative Coevolutionary algorithms in a multi-start framework.

Suggested Citation

  • Emile Glorieux & Bo Svensson & Fredrik Danielsson & Bengt Lennartson, 2017. "Constructive cooperative coevolution for large-scale global optimisation," Journal of Heuristics, Springer, vol. 23(6), pages 449-469, December.
  • Handle: RePEc:spr:joheur:v:23:y:2017:i:6:d:10.1007_s10732-017-9351-z
    DOI: 10.1007/s10732-017-9351-z
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    References listed on IDEAS

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    1. Hirsch, M.J. & Pardalos, P.M. & Resende, M.G.C., 2010. "Speeding up continuous GRASP," European Journal of Operational Research, Elsevier, vol. 205(3), pages 507-521, September.
    2. Jaco Schutte & Albert Groenwold, 2005. "A Study of Global Optimization Using Particle Swarms," Journal of Global Optimization, Springer, vol. 31(1), pages 93-108, January.
    3. R. Martí & J. Marcos Moreno-Vega & A. Duarte, 2010. "Advanced Multi-start Methods," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 265-281, Springer.
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    Cited by:

    1. Martín Montes Rivera & Carlos Guerrero-Mendez & Daniela Lopez-Betancur & Tonatiuh Saucedo-Anaya, 2023. "Dynamical Sphere Regrouping Particle Swarm Optimization: A Proposed Algorithm for Dealing with PSO Premature Convergence in Large-Scale Global Optimization," Mathematics, MDPI, vol. 11(20), pages 1-40, October.

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