考虑枢纽延误的集装箱公铁联运多目标路径优化  

Multi-objective Path Optimization of Container Road-rail Intermodal Transportation Considering Hub Delays

作　　者：段力伟 杨航 陈坚[1] DUAN Liwei;YANG Hang;CHEN Jian(College of Traffic&Transportation,Chongqing Jiaotong University,Chongqing 400074,China)

机构地区：[1]重庆交通大学,交通运输学院,重庆400074

出　　处：《交通运输系统工程与信息》2024年第6期275-285,共11页Journal of Transportation Systems Engineering and Information Technology

基　　金：教育部人文社会科学研究青年基金(18XJCZH001);重庆市交通科技项目(CQJT-CZKJ2024-05)。

摘　　要：为解决枢纽延误下的集装箱公铁联运路径优化问题,本文综合考虑运输中等待转运集装箱数量和铁路剩余能力的双重不确定性、枢纽转运能力上限及铁路发车要求对枢纽延误的影响,采用三角模糊数刻画不确定性,并从等待转运和等待班期两方面量化延误时间及其带来的碳排放和仓储成本。基于此,以路径方案总成本和总碳排放量最小化为目标,构建多目标路径优化模型,结合期望值法和模糊机会约束规划法对模型去模糊化,设计自适应快速非支配排序遗传算法(ANSGA-Ⅱ)求解模型,并引入模拟方法评估路径方案的可靠性,确定最佳置信度组合。结合某公铁联运网络开展的算例分析结果表明,相较于NSGA-Ⅱ算法,所提方法收敛速度更快,总成本和总碳排放量分别优化了2.03%和5.87%,且前沿解的可靠性均大于0.95,能为经营人决策路径方案提供有效支持。进一步的灵敏度分析显示,当等待转运集装箱数量达到某一特定值时,选择的运输方式更倾向于单一的公路运输,以降低因等待转运带来的枢纽延误;同时,枢纽延误对不同时间敏感度货物的路径选择也有不同影响。To address the path optimization problem in container road-rail intermodal transportation while considering hub delays,triangular fuzzy numbers are employed to characterize the uncertainty associated with such delays.This uncertainty takes into account the dual uncertainty in the number of containers awaiting transshipment and the remaining rail capacity in transport,as well as the limitations of hub transshipment capacity and rail departure requirements on hub delays.Therefore,the resulting delay time,along with the associated carbon emissions and storage costs,is quantified from the perspectives of waiting for transshipment and waiting for departure schedules.A multiobjective path optimization model is then developed to minimize the total cost and total carbon emissions associated with the path scheme.The model is de-fuzzified using the expected value method and fuzzy chance-constrained programming.A self-adaptive fast nondominated sorting genetic algorithm(ANSGA-II)is designed to solve the model.Additionally,the simulation methods are used to assess the reliability of the path scheme and to identify the optimal combination of confidence levels.The case study was conducted on a specific road-rail intermodal transportation network,and the results indicate that,compared to the NSGA-II algorithm,the proposed method exhibits a faster convergence speed.The total cost and total carbon emissions were improved by 2.03%and 5.87%,respectively,and the reliability of the frontier solutions was greater than 0.95.Further sensitivity analysis indicates that when the number of containers awaiting transfer reaches a specific threshold,the preferred mode of transport tends to shift towards single road transport.This adjustment aims to minimize hub delays caused by waiting for transfer.At the same time,hub delays also have different effects on the path selection of goods with different time sensitivity.

关 键 词：综合运输 路径优化 自适应快速非支配排序遗传算法 公铁联运 枢纽延误 可靠性 

分 类 号：U15[交通运输工程]