Multi-objective evolutionary algorithm based on neighborhood
一种基于邻域的多目标进化算法

Population maintenance is an important issue in multi-objective evolutionary algorithms. For the deficiency that the maintenance methods of good distribution usually have a high time complexity, a multi-objective evolutionary algorithm based on neighborhood (named NMOEA) was proposed. This measure defined a criterion-neighborhood containing relation, which represented the close degree of individuals. And it was used to assign diversity fitness in a dynamic method that maintained the population rapidly. By examining three performance metrics on seven test problems, the new algorithm can approach the true Pareto front fast, and has good distribution.