提出了一种基于分布估计算法(EDA)的座位优化控制模型.首先通过统计学习的手段建立解空间内个体分布的概率模型,然后对概率模型随机采样产生新的群体,如此反复进行,实现群体的进化,最终取得最优解.最后和遗传算法(GA)进行仿真对比.实验结果表明,采用分布估计算法求解多航段座位分配问题可以取得令人满意的解,而求解速度与遗传算法相比提升了近6倍. A seat optimization control model based on distribution estimation algorithm (EDA) is proposed.Firstly, the probability distribution model of individual distribution in solution space is established by means of statistical learning, and then a new population is generated by random sampling of probability model, so that the population Finally, it is compared with genetic algorithm (GA) .Experimental results show that a satisfactory solution can be obtained by using the distribution estimation algorithm to solve the multi-segment seat allocation problem, while the solution speed and genetic algorithm Than nearly six times the increase.