TY - GEN
T1 - The g-dominance Relation for Preference-Based Evolutionary Multi-Objective Optimization
AU - Luo, Wenjian
AU - Shi, Luming
AU - Lin, Xin
AU - Coello Coello, Carlos A.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - In evolutionary multi-objective optimization, the results generated by an evolutionary algorithm usually contain an approximation, as good as possible, of the entire Pareto-optimal front. However, sometimes the number of Pareto-optimal solutions may be so large that the decision maker (DM) is incapable of manipulating or understanding them. Methods for considering only the Pareto-optimal solutions that the DM prefers indeed constitute a hot research topic in the evolutionary computation field. In this paper, we introduce a new dominance relation called hat g-dominance, which is an improved version of the g-dominance relation and can be easily implemented in traditional multi-objective evolutionary algorithms. In this work, the proposed hat g-dominance is implemented in NSGA-II. Our experimental results show the effectiveness of hat g-NSGA-II with respect to the original g-NSGA-II.
AB - In evolutionary multi-objective optimization, the results generated by an evolutionary algorithm usually contain an approximation, as good as possible, of the entire Pareto-optimal front. However, sometimes the number of Pareto-optimal solutions may be so large that the decision maker (DM) is incapable of manipulating or understanding them. Methods for considering only the Pareto-optimal solutions that the DM prefers indeed constitute a hot research topic in the evolutionary computation field. In this paper, we introduce a new dominance relation called hat g-dominance, which is an improved version of the g-dominance relation and can be easily implemented in traditional multi-objective evolutionary algorithms. In this work, the proposed hat g-dominance is implemented in NSGA-II. Our experimental results show the effectiveness of hat g-NSGA-II with respect to the original g-NSGA-II.
KW - evolutionary computation
KW - g-dominance
KW - multi-objective optimization
KW - preference
UR - https://www.scopus.com/pages/publications/85071309319
U2 - 10.1109/CEC.2019.8790321
DO - 10.1109/CEC.2019.8790321
M3 - 会议稿件
AN - SCOPUS:85071309319
T3 - 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings
SP - 2418
EP - 2425
BT - 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Congress on Evolutionary Computation, CEC 2019
Y2 - 10 June 2019 through 13 June 2019
ER -