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Multiobjective Optimization Using Cross-Entropy Approach

Author

Listed:
  • Karim Sebaa
  • Abdelhalim Tlemçani
  • Mounir Bouhedda
  • Noureddine Henini

Abstract

A new approach for multiobjective optimization is proposed in this paper. The method based on the cross-entropy method for single objective optimization (SO) is adapted to MO optimization by defining an adequate sorting criterion for selecting the best candidates samples. The selection is made by the nondominated sorting concept and crowding distance operator. The effectiveness of the approach is tested on several academic problems (e.g., Schaffer, Fonseca, Fleming, etc.). Its performances are compared with those of other multiobjective algorithms. Simulation results and comparisons based on several performance metrics demonstrate the effectiveness of the proposed method.

Suggested Citation

  • Karim Sebaa & Abdelhalim Tlemçani & Mounir Bouhedda & Noureddine Henini, 2013. "Multiobjective Optimization Using Cross-Entropy Approach," Journal of Optimization, Hindawi, vol. 2013, pages 1-9, December.
    • Handle: RePEc:hin:jjopti:270623
    DOI: 10.1155/2013/270623
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    References listed on IDEAS

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    1. Bekker, James & Aldrich, Chris, 2011. "The cross-entropy method in multi-objective optimisation: An assessment," European Journal of Operational Research, Elsevier, vol. 211(1), pages 112-121, May.
    2. Rubinstein, Reuven Y., 1997. "Optimization of computer simulation models with rare events," European Journal of Operational Research, Elsevier, vol. 99(1), pages 89-112, May.
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