一种基于个体密度估算的多目标优化演化算法

通过在目标空间中利用目标本身信息估算个体k最近邻距离之和，作为个体的密度信息，根据个体的密度信息对群体中过剩的非劣解进行逐个去除，以便更好地维护解的多样性，由此给出了一种基于个体密度估算的多目标优化演化算法IDEMOEA。用这个算法对几个典型的多目标优化函数进行测试。测试结果表明，算法IDEMOEA求解多目标优化问题是行之有效的。

Multi-objective optimization evolutionary algorithm based on individual density estimation

A multi-objective optimization evolutionary algorithm based on Individual Density Estimation(IDEMOEA) is presented,which use the k nearest neighbors for individual density estimation by the information of objectives themselves in such a way that distances to the k nearest neighbors are summed together,namely individual density information,while prune the over-plus of non-dominated solutions in the population one by one according to individual density information with the purpose of preserving the diversity of solutions.A few of benchmark multi-objective optimization functions are tested.Experimental results demonstrate that the algorithm developed is efficient for solving multi-objective optimization problems.