A Surrogate-Assisted Cooperative Co-evolutionary Algorithm for Solving High Dimensional, Expensive and Black Box Optimization Problems

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Résumé

Many research efforts have been recently focus to solve large-scale global optimization (LSGO) problems by means of evolutionary algorithms. Cooperative co-evolution has been proposed to solve such problems depending on thousands of variables. This methodology has proved very efficient in solving a wide range of LSGO problems. Nevertheless, it often requires an extremely large number of function evaluations to reach a suitable solution. This is somewhat problematic when the function evaluation is computationally expensive. A globally effective approach to high-fidelity optimization problems based on such expensive analyses lies in the exploitation of surrogate models. They act as cheap-to-evaluate alternatives to the original high-fidelity models reducing the computational cost, while still providing improved designs. This kind of optimization process, referred to as surrogate-assisted optimization, has proved very efficient on small-dimensional problems but suffers from the curse of dimensionality to solve LSGO problems. In this paper, cooperative co-evolution was combined with surrogate-assisted optimization in order to efficiently solve high dimensional, expensive and black-box problems. Experimental results are provided on a wide set of benchmark problems and show promising results for the proposed algorithm.
langue originaleAnglais
Pages (de - à)41-52
Nombre de pages12
journalEngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization
Les DOIs
étatPublié - 14 sept. 2018
EvénementEngOpt2018: 6th International Conference on Engineering Optimization - Instituto Superior Tecnico, Libsonne, Portugal
Durée: 17 sept. 201819 févr. 2019
http://engopt2018.tecnico.ulisboa.pt/

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mots-clés

  • Global optimization
  • Surrogate-assisted optimization
  • Large-scale optimization
  • High dimensional
  • Expensive and black-box functions
  • Cooperative co-evolutionary algorithm
  • Random grouping
  • Genetic algorithm
  • Evolutionary algorithm

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