嵌入用户偏爱区域的多目标优化算法  

Multi-objective Optimization Algorithm Embedded by User Preference Region

作　　者：蒲保兴[1,2] 杨路明[1] 谢东[1] 

机构地区：[1]中南大学信息科学与工程学院,湖南长沙410083 [2]邵阳学院信息与电气工程系,湖南邵阳422001

出　　处：《小型微型计算机系统》2009年第1期144-147,共4页Journal of Chinese Computer Systems

基　　金：湖南省教育厅科研基金项目(05C671)资助;中南大学创新基金项目(ZB018)资助

摘　　要：针对已有的多目标优化方法在实际应用中存在的问题,给出了基于用户偏爱区域的多目标优化算法.它只求出与用户偏爱区域相关的部分Pareto最优集,从而减少了解的数量,加快了收敛速度.算法运用了精英非受控排序策略,并以个体与用户偏爱区域的距离作为影响适应值的一个因素,运用排挤策略实现解在Pareto边界分布的均匀性.仿真结果表明算法有效.Aiming at the problem of the existing multi-objective optimization methodologies in actual application, this paper proposes a multi-objective optimization algorithm based on user preference region, which only finds a preferred and smaller set of Pareto-optimal solutions, instead of the entire Pareto frontier, so that the number of solutions is reduced and the convergence rate is improved. The algorithm adopts the elitist non-dominated sorting strategy, takes the distance between individual and the user preference region as a factor affecting individualr s fitness, and applies the crowding strategy to maintain the diversity of solution. Simulation results show that the proposed algorithm is effective.

关 键 词：用户偏爱区域 多目标优化 PARETO最优集 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]