中文摘要：

利用参考点及角度值引入决策者的偏好信息，采用角度偏好区域设定方法将目标空间划分为偏好区域和非偏好区域，提出一种能区分偏好区域和非偏好区域中非支配解的支配策略——角度偏好的ε-Pareto支配策略．为验证所提出的支配策略的有效性，将其融入基于s支配的多目标进化算法（ε—MOEA）中，形成AP-ε-MOEA．通过与融入G支配的G—NSGA．II和融入R支配的R-NSGA—II的性能对比实验表明，AP-ε-MOEA在以较快速度收敛到Pareto最优边界的同时，能较好满足决策者偏好．

英文摘要：

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.