Sensitivity of performance evaluation results by inverted generational distance to reference points
Sensitivity of performance evaluation results by inverted generational distance to reference points
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DOI：
10.1109/cec.2016.7743912
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发表时间：
2016-07
期刊：
影响因子：
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通讯作者：
H. Ishibuchi;Hiroyuki Masuda;Y. Nojima
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文献类型：
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作者：
H. Ishibuchi;Hiroyuki Masuda;Y. Nojima
倒代距离（IGD）指标被广泛用于多目标算法的性能评价。在本文中，我们讨论了IGD的性能评价结果对参考点集规格的敏感性。通过计算实验，我们证明了使用IGD可以得到误导性的评估结果。产生误导性评价结果的原因是，IGD倾向于选择与参考点集分布相似的解决方案集。我们证明了IGD的这种不良偏差可以通过增加参考点集的大小和要比较的解集的大小来减小。研究还表明，使用一种改进的IGD指标，即逆代际距离加（IGD+），可以减少这种偏差。然而，随着目标数量的增加，这种偏见会变得更加严重。我们的实验结果清楚地表明，必须非常仔细地检查IGD和IGD+指标的性能比较结果。
The inverted generational distance (IGD) indicator has been frequently used for performance evaluation of many-objective algorithms. In this paper, we discuss the sensitivity of performance evaluation results by the IGD to the specification of a reference point set. Through computational experiments, we demonstrate that misleading evaluation results can be obtained by the use of the IGD. The reason for the misleading evaluation results is that the IGD tends to favor a solution set with a similar distribution to the reference point set. We demonstrate that such an undesirable bias of the IGD can be decreased by increasing the size of the reference point set and the size of solution sets to be compared. It is also shown that the bias can be decreased by using a modified IGD indicator called the inverted generational distance plus (IGD+). However, the bias becomes more severe by increasing the number of objectives. Our experimental results clearly demonstrate the necessity of very careful examination of performance comparison results by the IGD and IGD+ indicators.