DocumentCode :
2225931
Title :
A new non-redundant objective set generation algorithm in many-objective optimization problems
Author :
Guo, Xiaofang ; Wang, Yuping ; Wang, Xiaoli ; Wei, Jingxuan
Author_Institution :
School of Computer Science and Technology, Xidian University
fYear :
2015
fDate :
25-28 May 2015
Firstpage :
2851
Lastpage :
2858
Abstract :
Among the many-objective optimization problems, there exists a kind of problem with redundant objectives, it is possible to design effective algorithms by removing the redundant objectives and keeping the non-redundant objectives so that the original problem becomes the one with much fewer objectives. In this paper, a new non-redundant objective set generation algorithm is proposed. To do so, first, a multi-objective evolutionary algorithm based decomposition is adopted to generate a small number of representative non-dominated solutions widely distributed on the Pareto front. Then, the conflicting objective pairs are identified through these non-dominated solutions, and the non-redundant objective set is determined by these pairs. Finally, the experiments are conducted on a set of benchmark test problems and the results indicate the effectiveness and efficiency of the proposed algorithm.
Keywords :
Algorithm design and analysis; Approximation algorithms; Object recognition; Pareto optimization; Sociology; Evolutionary Algorithm; conflicting objectives; many-objective optimization; non-redundant objective set; objective reduction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2015 IEEE Congress on
Conference_Location :
Sendai, Japan
Type :
conf
DOI :
10.1109/CEC.2015.7257243
Filename :
7257243
Link To Document :
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