交通运输系统工程与信息

交通运输系统工程与信息 ›› 2019, Vol. 19 ›› Issue (4): 13-19.

• 综合交通运输体系论坛 • 上一篇    下一篇

混合不确定条件下绿色多式联运路径优化

李珺，杨斌*，朱小林   

  1. 上海海事大学物流研究中心，上海 201306
  • 收稿日期:2019-01-16 修回日期:2019-05-01 出版日期:2019-08-25 发布日期:2019-08-26
  • 作者简介:李珺(1991-)，女，河北衡水人，博士生.
  • 基金资助:

    国家自然科学基金/ National Natural Science Foundation of China(71471109)；上海市科委科研计划项目/ Shanghai Science and Technology Commission Research Project(17DZ2280200).

Path Optimization of Green Multimodal Transportation under Mixed Uncertainties

LI Jun, YANG Bin, ZHU Xiao-lin   

  1. Institute of Logistics Science & Engineering, Shanghai Maritime University, Shanghai 201306, China
  • Received:2019-01-16 Revised:2019-05-01 Online:2019-08-25 Published:2019-08-26

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摘要：

主要研究了当运输时间、中转时间、客户需求和中转集拼货运量四重混合不确定因素服从随机分布时的绿色多式联运路径优化问题，运用随机优化理论，以运输成本、碳排放成本和时间惩罚成本为目标，建立混合不确定条件下绿色多式联运路径优化模型.通过对各子目标函数权重进行赋值，得出考虑不同成本因素的多式联运路径优化方案.探讨时间、需求和网络服务能力对多式联运路径优化结果的灵敏度分析，发现各成本随时间变动而变化的规律和边际运输成本最小时的服务时间；当货运量形成规模效应后可降低边际运输成本；不同网络服务规模的运输路径优化结果，以及满足客户不确定需求的最小网络配置.

关键词: 综合交通运输, 路径优化, 四重混合不确定, 网络配置, 碳排放

Abstract:

When the quadruple mixed uncertainties of the transportation time, transit LCL time, customer demand and the transit freight volume are subject to stochastic distribution, the green multimodal transportation path optimization problem is researched. Using stochastic optimization theory, aiming at transportation cost, carbon emission cost and time penalty cost, a green multimodal transport path optimization model under mixed uncertainties is established. By assigning the weights of each sub-objective function, a multimodal transportation path optimization scheme considering different cost factors is obtained. The sensitivity analysis of time, demand and network service capabilities on the results of multimodal transport path planning is discussed. The law that each objective function cost changes with time, and service time when the marginal transportation cost is the smallest are obtained. The marginal transportation cost is reduced when the freight volume forms a scale effect. Transportation path optimization results for different network service scales and minimum network configurations to meet customer uncertain needs are received.

Key words: integrated transportation, path optimization, quadruple mixed uncertainties, network configuration, carbon emissions

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