摘要
车流量的波动变化是铁路运输工作中不可回避的现象,该现象必然会影响根据平均车流量得到的运输组织方案的真实性和有效性。本文以铁路枢纽编组站作业分工为背景,研究车流波动条件下运输组织优化问题的随机化构模方法,利用置信水平的概念将所建模型转化成一个概率意义上的最优化模型,提出了基于约束条件随机检验的复合遗传算法。仿真计算表明,提出的模型和算法能够有效地解决车流波动条件下铁路运输组织的优化问题。
The events of traffic undulation are usually occurred in railway industry, which will affect the reality and efficiency of the transport plan based on the average traffic volumes. This article studies the approach for formulating the optimal model of transport organization with traffic undulation using stochastic theory, with a case study of the task assignment among classification yards for railroad hubs. An optimal model with probability mode is presented by the accept level, and a hybrid genetic algorithm based on the random test of the conditions is proposed. The simulation results show that the model and algorithm developed here can solve effectively the problem of transport origination optimization with traffic undulation.
出处
《铁道学报》
EI
CAS
CSCD
北大核心
2003年第1期3-8,共6页
Journal of the China Railway Society
基金
兰州铁道学院青蓝人才工程资助
关键词
车流波动
随机优化
遗传算法
随机检验
编组站分工
铁路枢纽
traffic undulation
stochastic optimization
genetic algorithm
random test
task assignment of classification yards
railway hub
