摘要
本文研究铁路货运通道上的单组列车编组计划优化问题。货运通道是铁路网络中的骨干网,将已有的关于一般铁路网络的列车编组计划的研究结果应用于铁路货运通道时,由于在建模时未充分考虑铁路货运通道本身的特点以及车流特征,算力资源消耗较大且优化效果一般。针对上述问题本文建立了以时间成本为主要优化目标的铁路货运通道上的单组列车编组计划优化模型,并且为该模型设计了两种基于贪婪策略的迭代算法。通过数值实验表明,与常用的遗传算法比较,本文所采用的方法运算时间更短,且平均优化效果提升14%。
This paper studies the optimization problem of single-block train formation plan on railway corridor. Railway corridor is the backbone of the railway network. When applying the existing research results on train formation plan of general railway network to railway corridor, due to the characteristics of railway corridor itself and traffic flow are not fully considered in modeling, the computational resources consumption is large and the optimization effect is general. In order to solve the above problems, this paper establishes an optimization model of single-block train formation plan on the railway corridor with the time cost as the main optimization objective, and designs two iterative algorithms based on greedy strategy for the model. Numerical experiments show that, compared with the common genetic algorithm, the method adopted in this paper is faster and saves the time cost by more than 14% on average.
出处
《应用数学进展》
2020年第1期18-29,共12页
Advances in Applied Mathematics
基金
山西省自然科学基金201801D221193。
