Authors: Juan Zou Jinhua Zheng Cheng Deng Ruimin Shen
Publish Date: 2014/08/10
Volume: 19, Issue: 8, Pages: 2275-2286
Abstract
Multiobjective optimization is a challenging task in many disciplines Although a number of algorithms have simplified this problem by degenerating redundant objectives into lowdimensional sets there is currently no consensus method for evaluating their performance In this paper we propose an evaluation method that uses a spatial similarity ratio SSR to determine the quality of nonredundant objective sets NRSs We consider the reduction of all NRSs of three functions from 5D to 2D or 3D using our SSRbased method and compare the results to those given by an inverted generational distancebased method The results demonstrate that our method is more accurate as it takes information from both the nonredundant and redundant objective sets into consideration In addition using the proposed SSRbased approach no prior knowledge of the true Pareto set is required Therefore we can conclude that our SSRbased method is feasible for the assessment of nonredundant objective setsThe authors wish to thank the support of the Science and Technology Project of Hunan Province Grant No 2014GK3027 the National Natural Science Foundation of China Grant No 61379062 61372049 the Science Research Project of the Education Office of Hunan Province Grant No 12A135 12C0378 the Hunan Province Natural Science Foundation Grant No 14JJ2072 13JJ8006 the Hunan Provincial Innovation Foundation For Postgraduate Grant No CX2013A011 and the Construct Program of the Key Discipline in Hunan Province
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