基于公铁联运的高铁快运组织模式自动组合优化方法

Automatic combination and optimization method of high-speed railway express transport organization model based on intermodal transport

传统的高铁快运组织模式自动组合优化方法存在着经济效益差的缺陷,为此提出基于公铁联运的高铁快运组织模式自动组合优化方法研究。采用传感器对高铁快运组织模式自动组合运输成本数据进行采集,根据采集到的数据建立高铁快运运输需求模型,利用该模型得到高铁快运运输需求量。以得到的高铁快运运输需求量为依据,设定经济效益最大化为高铁快运组织模式自动组合为的优化目标,通过高铁快运组织模式自动组合优化算法实现了高铁快运组织模式自动组合的优化。通过100次1 500 km高铁快运组织模式自动组合货物运输实验得到,平均每次货物运输使用提出的高铁快运组织模式自动组合优化方法的高铁快运运输收益比传统方法高出19 709元,货主费用比传统方法降低132 942元,说明提出的高铁快运组织模式自动组合优化方法具备极高的有效性。

The traditional automatic combination optimization method of high-speed rail express transportation organization mode has the defect of poor economic benefit.Therefore,the automatic combination optimization method of high-speed rail express transportation organization mode based on public-rail intermodal transportation is proposed.The sensor is used to collect the cost data of high-speed rail express transportation,and the demand model of high-speed rail express transportation is established based on the collected data.The demand of high-speed rail express transportation is obtained by using the model.Based on the demand of high-speed rail express transportation,the optimization goal of automatic combination of high-speed rail express transportation organization modes is to maximize economic benefits.The optimization of automatic combination of high-speed rail express transportation organization modes is realized through the optimization algorithm of automatic combination of high-speed rail express transportation organization modes.Through 100 experiments of automatic combination of high-speed rail express transportation organization modes in 1 500 km,it is found that the average revenue of high-speed rail express transportation organization modes is 19709 yuan higher than that of traditional methods,and the cost of freight owners is 132942 yuan lower than that of traditional methods.This shows that the proposed method of automatic combination optimization of high-speed rail express transportation organization modes has very high performance effectiveness.