1st International Conference on Industrial Networks and Intelligent Systems

Research Article

Robust Differential Evolution for solving Numerical Optimization Problems

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  • @INPROCEEDINGS{10.4108/icst.iniscom.2015.258331,
        author={Chun Ling Lin and Sheng Ta Hsieh and Huang Lyu Wu and Tse Su},
        title={Robust Differential Evolution for solving Numerical Optimization Problems},
        proceedings={1st International Conference on Industrial Networks and Intelligent Systems},
        publisher={ICST},
        proceedings_a={INISCOM},
        year={2015},
        month={4},
        keywords={differential evolution elitist crossover optimization robust mutation vector},
        doi={10.4108/icst.iniscom.2015.258331}
    }
    
  • Chun Ling Lin
    Sheng Ta Hsieh
    Huang Lyu Wu
    Tse Su
    Year: 2015
    Robust Differential Evolution for solving Numerical Optimization Problems
    INISCOM
    ICST
    DOI: 10.4108/icst.iniscom.2015.258331
Chun Ling Lin1, Sheng Ta Hsieh2,*, Huang Lyu Wu2, Tse Su2
  • 1: Department of Electrical Engineering, Ming Chi University of Technology
  • 2: Department of Communication Engineering, Oriental Institute of Technology
*Contact email: fo013@mail.oit.edu.tw

Abstract

In this paper, the robust mutation strategy for differential evolution (DE) is proposed for Enhancing its solution searching abilities. Also, the elitist crossover is involved to produce potential vectors. In the experiments, fifteen CEC 2005 test functions, which include uni-modal and multi-modal functions, are adopted for testing the proposed method and compare its performance with three DE variants. From the results, it can be observed that the proposed method performs better than other DE approaches on most test functions.