Abstract: Population maintenance is an important issue in multi-objective evolutionary algorithms.For the traditional methods only concentrate on the distribution of solutions，a population maintenance strategy with both diversity and convergence considered is proposed.This measure assigns fitness with relative convergent relationship during neighboring individuals，which compensated the “coarseness” of the simple Pareto dominance relation effectively，and controlled crowding degree with an adjustable neighborhood method.Comparing with NSGA-II and SPEA2，this algorithm can maintain diversity of the population effectively，and have a good convergence and running time.

Key words: multi-objective evolutionary algorithm, multi-objective optimal problem, population maintenance, convergence, diversity

摘要： 种群维护是多目标进化算法的重要组成部分。针对传统方法在维护过程中只考虑分布性的情况，提出一种分布性与收敛性结合的种群维护策略，该方法用一种邻近个体间的相对趋近关系来表示其适应值，弥补了单纯Pareto支配关系的“粗糙性”，并用一种可调邻域的方法对种群的密集程度进行控制。将其与NSGA-II和SPEA2进行对比，实验结果表明该算法在有效保持种群分布性的同时，拥有良好的收敛性和速度。

关键词: 多目标进化算法, 多目标优化问题, 种群维护, 收敛性, 分布性