摘要
针对区间参数多目标优化问题,提出一种基于模糊支配的多目标粒子群优化算法.首先,定义基于决策者悲观程度的模糊支配关系,用于比较解的优劣;然后,定义一种适于区间目标值的拥挤距离,以更新外部存储器并从中选择领导粒子;最后,对多个区间多目标测试函数进行仿真实验,实验结果验证了所提出算法的有效性.
Aiming at multi-objective optimization problems with interval parameters, a multi-objective particle swarm optimization algorithm based on fuzzy dominance is proposed. Firstly, the fuzzy Pareto dominance relation based on decision-makers’ pessimism degree is defined for comparison of solutions. Then, the crowding distance suitable for interval objectives is defined for updating the external repository and selecting the global particle leaders. Finally, trials are carried out on several interval multi-objective benchmark testing functions, and the results show the effectiveness of the proposed algorithms.
出处
《控制与决策》
EI
CSCD
北大核心
2014年第12期2171-2176,共6页
Control and Decision
基金
国家自然科学基金项目(61074023
51175266)
江苏省科技支撑项目(BE2012175)
江苏省高校自然科学基金项目(12KJB510008)
江苏省普通高校研究生科研创新项目(KYZZ 0121)
关键词
多目标优化
区间参数
粒子群优化
模糊支配
multi-objective optimization
interval parameter
particle swarm optimization
fuzzy dominance
