摘要
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.
An optimal control model of seats based on estimation of distribution algorithm （EDA） is proposed. Firstly, the probability model of individual distribution in solution space is established by statistical learning. New populations are gotten by sampling the probability distribution randomly. The algorithm is iterated to realize the evolution and finally to get the best individuals. The algorithm is compared with genetic algorithm （GA） through simulation experiments. The experimental results show that the estimation of distribution algorithms can quickly obtain a satisfactory solution in solving multi-leg seat allocation problem, and the solving speed is 6 times as fast as that of genetic algorithm.
出处
《信息与控制》
CSCD
北大核心
2012年第6期774-778,785,共6页
Information and Control
关键词
收益管理
座位分配
分布估计算法
revenue management
capacity allocation
estimation of distribution algorithm
