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Evaluating Multiobjective Evolutionary Algorithms Using MCDM Methods

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  • Xiaobing Yu
  • YiQun Lu
  • Xianrui Yu

Abstract

The evaluation of multiobjective evolutionary algorithms (MOEAs) involves many metrics, it can be considered as a multiple-criteria decision making (MCDM) problem. A framework is proposed to estimate MOEAs, in which six MOEAs, five performance metrics, and two MCDM methods are used. An experimental study is designed and thirteen benchmark functions are selected to validate the proposed framework. The experimental results have indicated that the framework is effective in evaluating MOEAs.

Suggested Citation

  • Xiaobing Yu & YiQun Lu & Xianrui Yu, 2018. "Evaluating Multiobjective Evolutionary Algorithms Using MCDM Methods," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-13, March.
    • Handle: RePEc:hin:jnlmpe:9751783
    DOI: 10.1155/2018/9751783
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    Cited by:

    1. Fangzi Liu & Zihong Li & Hua Xie & Lei Yang & Minghua Hu, 2021. "Predicting Fuel Consumption Reduction Potentials Based on 4D Trajectory Optimization with Heterogeneous Constraints," Sustainability, MDPI, vol. 13(13), pages 1-33, June.
    2. Lei Yang & Wenbo Li & Simin Wang & Zheng Zhao, 2021. "Multi-Attributes Decision-Making for CDO Trajectory Planning in a Novel Terminal Airspace," Sustainability, MDPI, vol. 13(3), pages 1-25, January.
    3. Yu, Xiaobing & Duan, Yuchen & Luo, Wenguan, 2022. "A knee-guided algorithm to solve multi-objective economic emission dispatch problem," Energy, Elsevier, vol. 259(C).
    4. Chia-Chi Sun & Shih-Chi Chang, 2021. "An Assessment Framework for Solar Cell Material Based on a Modified Fuzzy DEMATEL Approach," Energies, MDPI, vol. 14(18), pages 1-17, September.

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