Abstract：A Delaunay triangulation based metric (DTDM) is proposed for assessing the diversity metric in multi-objective evolutionary algorithms (MOEAs) by analyzing the characteristics and shortcomings of the current diversity metrics. The proposed metric is introduced by combining the neighborhood-based ideology and distance-based ideology. The metric independently searches the neighborhood by using the properties of the nearest and adjacent neighborhood of Delaunay triangulation net. The non-dominated relationship is eliminated according to a space mapping technique. The experimental results show that the proposed metric accurately evaluates the diversity of the solution set obtained by MOEAs.
郑金华，王康，李密青，谢谆志. 基于Delaunay三角剖分的多目标进化算法解集分布度评价指标[J]. 模式识别与人工智能, 2012, 25(6): 885-893.
ZHENG Jin-Hua, WANG Kang, LI Mi-Qing, XIE Zhun-Zhi. A Delaunay Triangulation Based Diversity Metric for Solution Set of Multi-Objective Evolutionary Algorithms. , 2012, 25(6): 885-893.
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2012, Vol. 25 
