论文部分内容阅读
基于树枝形专用线取送车作业的特点,针对多次列车相继到达车站情况下各种车流到发方式的取送车问题建立统一的数学模型。对一种特殊的调移作业,即跨调作业,进行界定,并将其纳入模型的处理范围。该模型可根据问题的具体情况自适应的选择各种合理的取送作业方式,通过求解模型,可以得到合理的取送车顺序、取送批次和取送车时机。提出时距期望启发式信息的概念,它在准确刻画取送车流优先级别的同时,也被运用于算法的寻优过程,从而改善算法的求解效率。最后,针对模型的具体特点,设计模型解的编码方式,并采用基于云模型的参数自适应蚁群遗传算法进行仿真,结果表明了模型和算法的有效性。
Based on the characteristics of pick-and-place truck operation with tree-shaped special line, a unified mathematical model is established for the problem of pick-up vehicles with various train arrival and departure modes when multiple trains arrive at the station one after another. A special transfer operation, that is, cross-homework, is defined and included in the scope of the model. According to the specific situation of the problem, the model can choose various reasonable ways of picking and picking jobs. By solving the model, it is possible to get a reasonable sequence of pick-up carts, pick-up batches and pick-up carts timing. The concept of time-of-arrival heuristic information is proposed. It not only accurately depicts the priority of traffic flow but also applies to the optimization process of the algorithm, so as to improve the efficiency of the algorithm. Finally, according to the specific characteristics of the model, the coding mode of the model solution is designed and the model-based adaptive parameter-based ant colony genetic algorithm is used to simulate the model. The results show that the model and the algorithm are effective.