By using reference points and angle values, decision maker's preferences are introduced into ε-multi-objective evolutionary algorithm(ε-MOEA). The objective space is divided into preference area and non-preference area by the preferences. Moreover, an angle preference based ε-Pareto dominance strategy is presented. It establishes a strict partial order relation to distinguish the preference solutions and non-preference solutions among non-dominated solutions. To demonstrate the effectiveness of the proposed strategy, it is integrated into ε-MOEA,and thus ε-Pareto dominance strategy based on angle preference in MOEA(AP-ε-MOEA) is put forward . The comparative experiments of AP-ε-MOEA, g-dominance and r-dominance show that AP-ε-MOEA can converge to Pareto optimal front with a higher speed and meanwhile meet the decision maker′s preferences.
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