Abstract: For the problem that interactive genetic algorithms lack a way of measuring the uncertainty of evaluation，a method with grey level for discrete fitness is proposed to deal with this problem.Through analyzing the grey level of discrete fitness，information which reflecting the distribution of an evolutionary population is abstracted.Based on these，the adaptive probabilities of crossover and mutation operation of an evolutionary individual are presented.The algorithm is applied to a fashion evolutionary design system，the simulation results indicate that the algorithm can effectively resolve human fatigue and improve the performance of optimization.

摘要： 针对交互式遗传算法缺乏衡量评价不确定性的问题，采用离散适应值评价进化个体，利用灰度衡量评价的不确定性。通过确定离散适应值的灰度，获得反映种群进化分布的信息；基于此，给出了进化个体的自适应交叉和变异概率。将该算法应用于服装进化设计系统，仿真实例与分析结果表明，所提出的算法可以有效缓解人的疲劳，提高优化效率。