Two-Level Stable Matching-Based Selection in MOEA/D

• Published in: 2015 IEEE International Conference on Systems, Man, and Cybernetics pp. 1720 - 1725
• Main Authors: Mengyuan Wu, Sam Kwong, Qingfu Zhang, Ke Li, Ran Wang, Bo Liu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2015
• Subjects: Cities and towns; Convergence; Heuristic algorithms; Pareto optimization; Sociology
• DOI: 10.1109/SMC.2015.302

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.