摘要
基于NSGAⅡ框架,利用QEA的机制来保持多样性,同时引入分布估计二进制个体加快搜索的效率,本文提出了一个由量子计算启发的多目标演化算法(MOEA)——基于分布估计的多目标量子演化算法(记为EQMEA)。通过实例验证,EQMEA可以找到更接近与最优前沿的解,且解的分布更均匀。
Based on NSGA Ⅱ, a novel quantum inspired multi - objective evolutionary algorithm （called EQMEA） is proposed in this paper in which mechanism of QEA is used to keep diversity of population and estimation of distribution is introduced to accelerate efficiency. From examples we can find EQMEA can find better solutions and the solutions scatter homogeneously.
出处
《宜春学院学报》
2008年第2期61-63,106,共4页
Journal of Yichun University
关键词
量子进化算法
分布估计
多目标进化算法
Quantum inspired Evolutionary algorithm
Estimation of distribution
Multi- objective Evolutionary algorithm
