摘要
基于合作型协同进化模型,提出了一种新型的多目标优化进化算法。该算法使用精英保留的思想以加快收敛速度,并采用一种新型的子群体间合作方式,提高了候选解的多样性,且避免了在一般多目标优化进化算法中难以处理的适应值分配或非支配排序过程,从而大大减小了计算资源的消耗。使用图形法和三种定量的测度将所提算法与一种经典的多目标优化进化算法NSGA-Ⅱ在一组标准测试函数上进行了比较,结果表明算法具有更高的搜索效率。
A new multi - objective optimization evolutionary algorithm based on the model of cooperative co evolution is proposed in this paper. The algorithm incorporates the idea of elitism to motivate convergence, and adopts a novel form of collaboration between subpopulations, which improves its ability to keep diversity and avoids the difficult process of fitness assignment or non - dominance ranking in general multi - objective evolutionary algorithms so that the computational cost is greatly reduced. The proposed algorithm is compared with a well - known multi - objective evolutionary algorithm NSGA - Ⅱ on a suite of standard test functions using visual graphs and three quantitative metrics. Results indicate that this algorithm can search more effectively.
出处
《计算机仿真》
CSCD
2007年第2期157-161,共5页
Computer Simulation
基金
国家自然科学基金项目(60474034
60474019)
关键词
协同进化
多目标优化
进化算法
精英保留
Co - evolution
Multi - objective optimization
Evolutionary algorithm
Elitism preservation
作者简介
申晓宁（1981-），女（汉族），江苏南京人，博士研究生，研究领域为进化算法，多目标优化。
胡维礼（1941一），男（汉族），江苏东台人，博士生导师，教授，研究领域为智能控制，网路控制系统，机器人控制，数字交流伺服系统。
