caa a22 4500 605470286 CHVBK 20210128100327.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s00500-014-1409-3 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1409-3 An evaluation of non-redundant objective sets based on the spatial similarity ratio [Elektronische Daten] [Juan Zou, Jinhua Zheng, Cheng Deng, Ruimin Shen] Multi-objective optimization is a challenging task in many disciplines. Although a number of algorithms have simplified this problem by degenerating redundant objectives into low-dimensional 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 non-redundant objective sets (NRSs). We consider the reduction of all NRSs of three functions from 5D to 2D or 3D using our SSR-based method, and compare the results to those given by an inverted generational distance-based method. The results demonstrate that our method is more accurate, as it takes information from both the non-redundant and redundant objective sets into consideration. In addition, using the proposed SSR-based approach, no prior knowledge of the true Pareto set is required. Therefore, we can conclude that our SSR-based method is feasible for the assessment of non-redundant objective sets. Springer-Verlag Berlin Heidelberg, 2014 Multi-objective optimization nationallicence Redundant objective reduction algorithm nationallicence Non-redundant objective sets nationallicence Spatial similarity ratio nationallicence Evaluation methodology nationallicence Zou Juan Information Engineering College of Xiangtan University, Xiangtan, Hunan Province, China aut Zheng Jinhua Information Engineering College of Xiangtan University, Xiangtan, Hunan Province, China aut Deng Cheng Information Engineering College of Xiangtan University, Xiangtan, Hunan Province, China aut Shen Ruimin Information Engineering College of Xiangtan University, Xiangtan, Hunan Province, China aut Soft Computing Springer Berlin Heidelberg 19/8(2015-08-01), 2275-2286 1432-7643 19:8<2275 2015 19 500 https://doi.org/10.1007/s00500-014-1409-3 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1409-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zou Juan Information Engineering College of Xiangtan University, Xiangtan, Hunan Province, China aut NATIONALLICENCE 700 1- Zheng Jinhua Information Engineering College of Xiangtan University, Xiangtan, Hunan Province, China aut NATIONALLICENCE 700 1- Deng Cheng Information Engineering College of Xiangtan University, Xiangtan, Hunan Province, China aut NATIONALLICENCE 700 1- Shen Ruimin Information Engineering College of Xiangtan University, Xiangtan, Hunan Province, China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/8(2015-08-01), 2275-2286 1432-7643 19:8<2275 2015 19 500