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    王新宇

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    • 性别:男
    • 毕业院校:大连理工大学
    • 学位:博士
    • 所在单位:机械工程学院
    • 电子邮箱:seringwang@dlut.edu.cn

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    A modified hypervolume based expected improvement for multi-objective efficient global optimization method

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    论文类型:期刊论文

    发表时间:2018-11-01

    发表刊物:STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION

    收录刊物:SCIE

    卷号:58

    期号:5

    页面范围:1961-1979

    ISSN号:1615-147X

    关键字:Multi-objective; Efficient global optimization; Pareto points; Hypervolume indicator

    摘要:The hypervolume indicator has been proved as an outstanding metric for the distribution of Pareto points, and the derived hypervolume based expected improvement (HVEI) has received a particular attention in the multi-objective efficient global optimization (EGO) method. However, the high computational cost has become the bottle neck which limits the application of HVEI on many objective optimization. Aiming at this problem, a modified version of HVEI (MHVEI) is proposed in this paper, which is easier to implement, maintains all the desired properties, and has a much lower computational cost. The theoretical study shows that the new criterion can be considered as a weighted integral form of HVEI, and it prefers the new point with a higher uncertainty compared with HVEI. The numerical tests show that the MHVEI performs similar as HVEI on the lower dimensional problem, and the advantage of MHVEI becomes more obvious as the dimension grows.