摘要
区间多目标优化问题在实际应用中普遍存在且非常重要.为得到贴合决策者偏好的最满意解,采用边优化边决策的方法,提出一种交互进化算法.该算法通过请求决策者从部分非被支配解中选择一个最差解,提取决策者的偏好方向,基于该偏好方向设计反映候选解逼近性能的测度,将具有相同序值和决策者偏好的候选解排序.将所提方法应用于4个区间2目标优化问题,并与利用偏好多面体解决区间多目标优化问题的进化算法(PPIMOEA)和后验法比较,实验结果验证了所提出方法的有效性和高效性.
Interval multi-objective optimization problems are ubiquitous and important in real-world applications. An interactive evolutionary algorithm incorporating an optimization-cum-decision-making procedure is presented to obtain the most preferred solution that fits a decision-maker（DM）＇s preferences. In this algorithm, a preference direction is elicited by requesting the DM to select the worst one from a part of non-dominated solutions. A metric based on the above direction, which reflects the approximation performance of a candidate solution, is designed to rank different solutions with the same rank and preference. The proposed method is applied to four interval bi-objective optimization problems, and compared with PPIMOEA as well as a posteriori method. The experimental results show the effectiveness and high efficiency of the proposed method.
出处
《控制与决策》
EI
CSCD
北大核心
2013年第4期542-546,共5页
Control and Decision
基金
国家自然科学基金项目(61105063)
中国矿业大学培育学科创新能力提升基金项目(2011XK09)
淮海工学院自然科学基金项目(KQ12015)
关键词
进化算法
交互
多目标优化
区间
偏好方向
evolutionary algorithm
interaction
multi-objectiveoptimization
interval
preference direction
