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基于随机权和的多目标进化算法
Multi-objective Evolutionary Algorithm Based on Random Weight-Sum Method
【摘要】 在多目标进化算法理论和应用研究进展的基础上,通过采用外部群体的精英保留策略并引入拥挤距离来保持群体多样性的策略,设计了一种基于随机生成权向量的加权和函数的多目标进化算法。用所提出的方法求解若干常用的测试函数,并与NAGS-II进行比较,结果表明了算法的有效性。
【Abstract】 On the basis of recent theory and application development of MOEAs,a new MOEA which utilizing the aggregated function of randomly generated weight vectors is presented.This proposed method adopts an external population to perform elitism and preserve diversity in the population by using the idea of crowding distance.The effectiveness of the suggested algorithm is demonstrated by performing some numerical experiments on some commonly used benchmark problems problem instances and comparing its results against NSGA-II.
【关键词】 多目标目标进化算法;
加权和方法;
Pareto-最优解;
Pareto-前沿;
【Key words】 multi-objective evolutionary algorithm; weight-sum method; Pareto-optimal solution; Pareto-front;
【Key words】 multi-objective evolutionary algorithm; weight-sum method; Pareto-optimal solution; Pareto-front;
【基金】 国家自然科学基金资助项目(70301005);教育部南开-天津大学刘徽应用数学中心资助项目。
- 【文献出处】 计算机工程与应用 ,Computer Engineering and Applications , 编辑部邮箱 ,2006年32期
- 【分类号】TP18
- 【被引频次】10
- 【下载频次】177