运筹与管理 ›› 2024, Vol. 33 ›› Issue (4): 35-41.DOI: 10.12005/orms.2024.0109

• 理论分析与方法探讨 • 上一篇    下一篇

带服务时间窗的绿色多式联运路径和速度多目标优化

吴鹏1, 季海涛1, 林峰1, 程俊恒2   

  1. 1.福州大学 经济与管理学院,福建 福州 350108;
    2.福建师范大学 经济学院,福建 福州 350107
  • 收稿日期:2021-10-10 出版日期:2024-04-25 发布日期:2024-06-13
  • 通讯作者: 吴鹏(1987-),通讯作者,男,江西丰城人,博士,教授,博士生导师,研究方向:智能交通管理,运筹与管理。
  • 作者简介:季海涛(1996-),男,安徽无为人,硕士研究生,研究方向:交通运输优化;林峰(1991-),男,福建宁德人,博士,讲师,硕士生导师,研究方向:物流与供应链管理;程俊恒(1988-),女,湖南醴陵人,博士,副教授,硕士生导师,研究方向:工业工程与管理,金融工程。
  • 基金资助:
    国家自然科学基金资助项目(71871159,71901069);教育部人文社科规划基金项目(21YJA630096)

Route and Speed Multi-objective Optimization for Green Intermodal Transportation with Service Time Window

WU Peng1, JI Haitao1, LIN Feng1, CHENG Junheng2   

  1. 1. School of Economics and Management, Fuzhou University, Fuzhou 350108, China;
    2. School of Economics, Fujian Normal University, Fuzhou 350107, China
  • Received:2021-10-10 Online:2024-04-25 Published:2024-06-13

摘要: 在货物运输中,除考虑传统的成本目标外,最小化其对环境的影响具有重要的意义。本文研究了一类新的带服务时间窗的绿色公海多式联运多目标优化问题,旨在多式联运网络中决策货物运输路径和速度以满足货物运输需求,目的是同时最小化货物运输总成本和碳排放总量,并建立该问题的多目标混合整数非线性规划模型。为有效求解该问题,将上述非线性模型转化为线性模型,并提出了一种基于ε-约束法和模糊逻辑相结合的算法。最后以我国典型的绿色多式联运问题为例对模型和算法的有效性进行验证。计算结果表明,所提出的模型和算法能够有效求解所提出的带服务时间窗的绿色多式联运多目标优化问题,为决策者在进行绿色多式联运的路径和速度决策时提供参考。

关键词: 服务时间窗, 绿色多式联运, 路径优化, 速度优化, ε-约束法

Abstract: The vigorous development of the economy is driving the construction of a strong transportation country in China. With the continuous promotion of the “the Belt and Road” and “Regional Economic Belt” strategies, such as the opening of container transport channels such as “China Europe Express” and “Yangtze River Economic Belt”, China’s intermodal transport also has ushered in a historic development opportunity. At the same time, the continuous intensification of the global greenhouse effect and the increasing awareness of low-carbon environmental protection among people have also prompted China to accelerate the construction of a green transportation system and reduce its impact on the environment, which puts forward higher requirements for reducing the carbon emissions generated by intermodal transportation. However, the current market share of intermodal container transportation in China is still relatively small and the development speed is slow. The main reason is that shippers do not have an enough understanding of the relevant situation of intermodal container transportation, and the marketing work of intermodal transportation operators is not yet in place. Therefore, people are increasingly interested in developing intermodal transportation solutions, which requires a shift towards railway or sea transportation modes. This is particularly true of China, which has navigable waterways including vast coastal and inland waterways. Coastal and short distance sea transportation can be utilized for cargo transportation, with a focus on alleviating congestion in existing road and railway infrastructure. Therefore, how to plan transportation plans reasonably to improve freight efficiency, effectively integrate resources, and achieve low-cost and green transportation while meeting the diverse needs of shippers, time window constraints, and multi cargo logistics is an in-depth research question of this article.
With regard to freight transportation and in addition to optimizing traditional cost objective, minimizing the negative impact on the environment is also of great significance. This paper studies a new multi-objective green road-sea intermodal transportation problem with service time windows, which aims to determine the freight transport route and speed in the intermodal transportation network to meet transport demands. The objective is to simultaneously minimize the total cost and carbon emissions. For this problem, a multi-objective mixed integer programming model is first developed. To effectively and efficiently solve this problem, a new ε-constraint method combined with a fuzzy-logic method is proposed. Then, the effectiveness of the proposed model and algorithm is verified by a typical green intermodal transport problem in China. The computational results show that the proposed model and algorithm can efficiently and effectively solve the proposed multi-objective optimization problem of green intermodal transport with service time windows. Compared with truck transport, the use of intermodal transport can reduce the cost by 33.91%, which is of great significance for the conversion from road transport to road-sea intermodal transport. In addition, The cases are analyzed, where decision-makers have different preferences and there are changes in fuel prices, to provide a reference for decision-makers when optimizing route and speed in green intermodal.
This article conducts some research on the optimization of green intermodal transportation paths and speeds with service time windows. However, due to time constraints and limitation of our own knowledge, there are still some shortcomings in some aspects. Therefore, considering the future development of green intermodal transportation, the following aspects are still worth further research, including excluding other negative factors that may exist in transportation, such as traffic congestion, weather conditions during ship navigation, and terrain. Therefore, in the future, it is necessary to deeply analyze the impact of various factors on shipping plans in green intermodal transportation issues.

Key words: service time window, green intermodal transportation, route optimization, speed optimization, ε-constraint method

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