DocumentCode :
3728198
Title :
Two-Level Stable Matching-Based Selection in MOEA/D
Author :
Mengyuan Wu;Sam Kwong;Qingfu Zhang;Ke Li;Ran Wang;Bo Liu
Author_Institution :
Dept. of Comput. Sci., City Univ. of Hong Kong, Hong Kong, China
fYear :
2015
Firstpage :
1720
Lastpage :
1725
Abstract :
Stable matching-based selection models the selection process in MOEA/D as a stable marriage problem. By finding a stable matching between the sub problems and solutions, the solutions are assigned to sub problems to balance the convergence and the diversity. In this paper, a two-level stable matching-based selection is proposed to further guarantee the diversity of the population. More specifically, the first level of stable matching only matches a solution to one of its most preferred sub problems and the second level of stable matching is responsible for matching the solutions to the remaining sub problems. Experimental studies demonstrate that the proposed selection scheme is effective and competitive comparing to other state-of-the-art selection schemes for MOEA/D.
Keywords :
"Convergence","Sociology","Pareto optimization","Heuristic algorithms","Cities and towns"
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/SMC.2015.302
Filename :
7379434
Link To Document :
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