换挂模式下的公路卡车货运优化问题

Optimization problem of truck freight transportation with trailer-swapping mode

本文深入研究了换挂模式在公路卡车货运中的应用,通过卡车间的挂车交换,有效减少卡车空载现象,进而降低运输总成本。为了探讨卡车个体特征对换挂模式的影响,基于一般换挂模式扩展了受限换挂模式,并构建了两种模式下公路卡车货运优化问题的混合整数线性规划模型。该模型旨在最小化卡车的总成本,包括卡车运输成本和货物延迟送达惩罚成本。鉴于原模型无法在可接受的时间内求得问题最优解,引入两个辅助参数,将原模型转换为纯整数规划模型。然而,受限换挂模式下的卡车个体收益四维约束求解难度依然很大,因此,基于卡车潜在换挂节点集和节点潜在换挂卡车集的分析,对卡车个体收益约束进行了拆分和删减。实验结果显示,相较于传统模式,一般换挂模式和受限换挂模式在降低总成本、减少油耗、降低卡车空载率、缩短行驶时间方面均取得显著效果,具体地,两种模式分别使总成本平均降低28.3%和25.1%,油耗减少33.3%和29.7%,空载率下降33.1%和29.4%,行驶时间缩短35.0%和27.6%。然而,换挂模式在货物时效性方面略显不足,延迟送达率平均为15.4%和12.9%。此外,一般换挂模式下,部分卡车的行驶时间会略微延长,平均增长率为7.4%。最后,卡车空载系数灵敏度分析结果显示,在不同系数下换挂模式的性能仍然显著。

This study examines the application of the trailer-swapping mode(TSM)in truck freight transportation,which effectively reduces truck empty rates and overall transportation costs through the swapping of trailers between trucks.To explore the influence of individual truck characteristics on the TSM,this study develops a restricted TSM(RTSM)based on the general TSM(GTSM),and a mixed integer linear programming model is constructed to solve the optimization problem of truck freight transportation under both modes.The model objective is to minimize the total cost of trucks,including transportation costs and penalties for delayed delivery of goods.Given the inability of the original model to obtain the optimal solution within an acceptable time,we introduce two auxiliary parameters to transform the model into a pure integer programming model.However,the four-dimensional constraints of truck individual revenue under the RTSM still pose significant challenges.Therefore,based on the analysis of the potential swapping nodes and truck sets,the constraints on truck individual revenue are split and reduced.Numerical experiment results indicate that compared to the traditional mode,the GTSM and the RTSM achieve significant reductions in total costs,fuel consumption,empty ruck rates,and travel time by 28.3%and 25.1%,33.3%and 29.7%,33.1%and 29.4%,and 35.0%and 27.6%,respectively.However,the TSM displays a slight deficiency in delivery timeliness,with average delayed delivery rates of 15.4%and 12.9%,respectively.Additionally,under the GTSM,the travel time of some trucks increases slightly,with an average increase of 7.4%.Finally,sensitivity analysis of the truck empty rate coefficient documents the significant performance of the TSM under different coefficients.