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论文类型：期刊论文

发表时间：2016-10-01

发表刊物：STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION

收录刊物：SCIE、EI、Scopus

卷号：54

期号：4

页面范围：1093-1105

ISSN号：1615-147X

关键字：Diversity; Competitiveness; Performance compromise; Performance penalty

摘要：This paper studies the problem of balancing diversity and performance in surrogate-based global optimization when we look for two diverse competitive designs. A previous formulation that maximizes the average performance of the two designs with constraint on diversity is compared to a new formulation that maximizes diversity for a given loss in performance with respect to a single global optimum. The loss in performance is estimated using the surrogate. Three test functions are used to compare the curves of diversity vs. performance obtained from the two formulations. Significantly, for the examples, the search for the two diverse designs produced also designs much closer in performance to the global optimum than the two designs satisfying the diversity constraint or goal. Therefore, if three designs are accepted as the outcome of the search, the loss of performance may be drastically reduced.