一类带有随机参数的交通优化模型及遗传算法

双向编组站包含两个个独立的作业系统，确定最合理的系统分工方案是这类编组站必须解决的首要问题，车流量则是该问题重要的输入参数，在实际运输工作中，车流量随着时间的不同总要发生一定的波动变化，这必然会影响双向编组站系统分工方案，针对这一交通运输学科经常面临的情况，构造了车流波动条件下双向编组站系统作为分工的随机优化模型，建立了基于遗传算法的求解理论，该方法对交通问题具有一般性的意义。

Class of traffic optimization model with stochastic parameters and genetic algorithm

Two operation systems are included by bidirectional classification yards, it is essential to determine the most rational plan for division of work of systems. The traffic volume is an important input to any these transport problems. Actually, the traffic volumes are usually undulated with the passage of time, and this phenomenon will affect the plan for division of work of systems at bidirectional classification yard. In accordance with this situation which being always encountered in traffic and transportation, this paper builds a new stochastic optimization model for division of work of systmes at bidirectional classification yard with traffic volume undulation. At last, a solution procedure for this problem based on Genetic Algorithm is presented. This approach has general significance for other similar transport problem.