不确定运价下长江集装箱多式联运路径优化

doi:10.3969/j.issn.1007-7375.220245

摘要/Abstract

摘要： 为充分贴合长江集装箱多式联运场景，在分析长江多式联运组织特点的基础上，考虑不确定运价及不同航段航道通航条件影响，以包含运输周转成本、碳排放成本和时间成本在内的总成本最小化为目标，构建不确定条件下长江集装箱多式联运路径优化模型，并设计蒙特卡洛仿真与改进的狼群算法实现模型求解，最后通过算例分析验证改进的狼群算法的有效性。算例分析结果表明，公路运输能有效控制运输的时间成本，铁路与水路运输在运输经济性与绿色性方面更具优势。在长江航道通航能力与最大中转次数限制下，运输任务将选择较高成本运输方案以满足航道与托运人要求。

关键词: 集装箱运输, 多式联运, 不确定运价, 蒙特卡洛仿真, 狼群算法, 路径优化

Abstract: In order to fully adapt to scenario of container multimodal transportation in the Yangtze River, on the basis of analyzing the characteristics of such scenario, the impact of uncertain freight rates and navigation conditions of different route segments are taken into account in this paper. A route optimization model for container multimodal transportation in the Yangtze River with uncertain conditions is built with the objective of minimizing the total cost including transportation turnover cost, carbon emission cost and time cost. Also, a Monte Carlo simulation and an improved wolf colony algorithm are designed to solve the model. Finally, an example is given to verify the effectiveness of the improved wolf colony algorithm. The analysis results of the example show that highway transportation can effectively control the time cost of transportation, while railway and waterway transportation have more advantages in transportation economy and greenness. Considering the navigation capacity and the maximum number of transfers of the Yangtze River waterway, the transportation task may choose a transportation scheme with higher cost to meet the requirements of the waterway and shippers.

Key words: container transportation, multimodal transportation, uncertain freight rate, Monte Carlo simulation, wolf colony algorithm, path optimization

中图分类号:

李俊, 温想, 梁晓磊. 不确定运价下长江集装箱多式联运路径优化[J]. 工业工程, 2024, 27(2): 138-146.

LI Jun, WEN Xiang, LIANG Xiaolei. Route Optimization of Multimodal Transportation for Containers in the Yangtze River with Uncertain Freight Rates[J]. Industrial Engineering Journal, 2024, 27(2): 138-146.

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