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.
出处
《小型微型计算机系统》
CSCD
北大核心
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
