Preference-Inspired Co-evolutionary Algorithm Based on Hybrid Domination Strategy
WANG Liping1,2, DU Jiejie1,2, QIU Feiyue3, JIANG Bo3
1.College of Economics and Management, Zhejiang University of Technology, Hangzhou 310023 2.Institute of Information Intelligence and Decision Optimization, Zhejiang University of Technology, Hangzhou 310023 3.College of Education, Zhejiang University of Technology, Hangzhou 310023
Abstract:The preference-inspired co-evolutionary algorithm employing goal vectors can not identify the Pareto dominance relationship of candidate solutions at the same fitness level, and the obtained solutions are unevenly distributed along the Pareto front. Aiming at these problems, preference-inspired co-evolutionary algorithm based on hybrid domination strategy(E-PICEA-g) is proposed in this paper. Firstly, Pareto dominance sorting on population is conducted, and then the candidate solutions fitness values are calculated to reduce the proportion of non-dominated solutions in the population and increase the selection pressure. Meanwhile, the distance between candidate solutions and ideal point is considered to punish the candidate solutions at the same fitness level but far from the ideal point. Thus, the obtained solutions are made to distribute evenly along the Pareto optimal front. Experimental results on 12 multi-objective optimization functions demonstrate that the proposed algorithm acquires solutions with high quality on most of the test functions.
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