排放控制区下集装箱班轮运输船期设计与燃油补给联合优化

doi:10.16097/j.cnki.1009-6744.2022.01.029

交通运输系统工程与信息 ›› 2022, Vol. 22 ›› Issue (1): 273-281.DOI: 10.16097/j.cnki.1009-6744.2022.01.029

排放控制区下集装箱班轮运输船期设计与燃油补给联合优化

李德昌，杨华龙^*，赵帅奇，郑建风

大连海事大学，交通运输工程学院，辽宁大连 116026

收稿日期:2021-09-23 修回日期:2021-11-29 接受日期:2021-12-01 出版日期:2022-02-25 发布日期:2022-02-23
作者简介:李德昌(1994- )，男，山东德州人，博士生。
基金资助:
国家自然科学基金

Joint Optimization of Vessel Scheduling and Refueling for Container Liner Shipping in Emission Control Areas

LI De-chang, YANG Hua-long^* , ZHAO Shuai-qi, ZHENG Jian-feng

Transportation Engineering College, Dalian Maritime University, Dalian 116026, Liaoning, China

Received:2021-09-23 Revised:2021-11-29 Accepted:2021-12-01 Online:2022-02-25 Published:2022-02-23
Supported by:
National Natural Science Foundation of China(72071024，71871036)。

摘要/Abstract

摘要： 为解决排放控制区下集装箱班轮运输船期设计和燃油补给联合优化问题，分析了多时间窗、多起讫时间和多装卸效率等合作协议条款与船舶航行、装卸及到/离港时间之间的关联性。结合燃油补给港燃油价格差异和折扣因素，以船公司航线服务周总成本最小化为目标，构建排放控制区下船期设计和燃油补给混合整数非线性规划模型，设计线性割线近似的求解方法。以中远海运集团有限公司AWE1航线为例，数值实验验证了模型及其求解方法的适用性和有效性。结果显示：船期设计与燃油补给联合优化可使船公司航线服务周总成本降低7.41%；随着船舶到港时间窗长度的增大，船公司航线服务周总成本及船舶在排放控制区内平均航速均随之降低。研究表明，上述合作协议条款不仅有助于船公司更为灵活地调整船舶航速和船期，还有利于减少船舶在排放控制区内的温室气体排放。

关键词: 水路运输, 集装箱班轮运输, 混合整数非线性规划模型, 船期设计, 燃油补给, 排放控制区

Abstract: This paper investigates the vessel scheduling and refueling for container liner shipping in emission control areas. The relationship between the terms of cooperation agreements was analyzed including multiple time windows, multiple start/end times, multiple loading/unloading rates, and the time of vessel sailing, loading/unloading, and arrival/ departure. In accordance with the factors of fuel price differentiation and its discount at different ports, the vessel scheduling and refueling problem with emission control was formulated as a mixed integer non-linear programming model, which has the goal of minimum total weekly route service cost of liner shipping. The linear secant approximation was also designed to solve the model. Taking the AWE1 route served by China COSCO Shipping Corporation Limited as an example, the paper verified the applicability and effectiveness of the model and the solution method by numerical experiments. The results show that the joint optimization of vessel scheduling and refueling of liner shipping would reduce the total weekly route service cost by 7.41%. The total weekly route service cost and the average vessel sailing speed in emission control areas would decrease with the increase of the length of vessel arrival time window. The result indicates that the terms of cooperation agreement would not only help shipping companies to adjust vessel sailing speed and schedule with more flexibility, but also help reducing vessels’greenhouse gas emissions in emission control areas.

Key words: waterway transportation, container liner shipping, mixed integer non- linear programming model, vessel scheduling, refueling, emission control areas

中图分类号:

U692.3

李德昌, 杨华龙, 赵帅奇, 郑建风. 排放控制区下集装箱班轮运输船期设计与燃油补给联合优化[J]. 交通运输系统工程与信息, 2022, 22(1): 273-281.

LI De-chang, YANG Hua-long , ZHAO Shuai-qi, ZHENG Jian-feng. Joint Optimization of Vessel Scheduling and Refueling for Container Liner Shipping in Emission Control Areas[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 273-281.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.tseit.org.cn/CN/10.16097/j.cnki.1009-6744.2022.01.029

http://www.tseit.org.cn/CN/Y2022/V22/I1/273

参考文献

[1] DE A, CHOUDHARY A, TURKAY M, et al. Bunkering policies for a fuel bunker management problem for liner shipping networks[J]. European Journal of Operational Research, 2021, 289(3): 927-939.

[2] DULEBENETS M A. The green vessel scheduling problem with transit time requirements in a liner shipping route with emission control areas[J]. Alexandria Engineering Journal, 2018, 57: 331-342.

[3] WANG C, CHEN J. Strategies of refueling, sailing speed and ship deployment of containerships in the low-carbon background[J]. Computers & Industrial Engineering, 2017, 114: 142-150.

[4] 楚金华, 李俊鹤, 王春娟, 等. 排放控制区下集装箱班轮航线路径规划与航速调度集成决策[J]. 交通运输系统工程与信息, 2021, 21(4): 230-238, 262. [CHU J H, LI J H, WANG C J, et al. Integrated decision on route planning and speed scheduling of container liners considering emission control areas[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(4): 230-238, 262.]

[5] ALHARBI A, WANG S, DAVY P. Schedule design for sustainable container supply chain networks with port time windows[J]. Advanced Engineering Informatics, 2015, 29(3): 322-331.

[6] LIU Z, WANG Z, DU Y, et al. Supply chain cost minimization by collaboration between liner shipping companies and port operators[J]. Transportation Journal, 2016, 55(3): 296-314.

[7] DULEBENETS M A. Minimizing the total liner shipping route service costs via application of an efficient collaborative agreement[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 20(1): 123- 136.

[8] 杨华龙, 李德昌, 宋巍, 等. 考虑船舶航速偏离的集装箱班轮运输货运收益鲁棒优化[EB/OL]. 中国管理科学 (2021-04-01)[2021-09-23], https://doi.org/10.16381/j. cnki.issn1003- 207x.2020.1298. [YANG H L, LI D C, SONG W, et al. Freight revenue robust optimization for container liner shipping considering vessel sailing speed deviation[EB/OL]. Chinese Journal of Management Science (2021- 04- 01) [2021- 09- 23], https://doi.org/ 10.16381/j.cnki.issn1003-207x.2020.1298.]

[1]	杨华龙, 吴艳华, 孙奕伦. 多品种燃油海运库存路径问题鲁棒优化模型与算法[J]. 交通运输系统工程与信息, 2022, 22(3): 238-246.
[2]	吕靖, 齐海迪, 李宝德. 基于扩展置信规则库的海盗袭击事件风险预测[J]. 交通运输系统工程与信息, 2022, 22(3): 247-254.
[3]	廖诗管, 翁金贤, 胡甚平. 液化天然气船通航模式下的航道通过能力评价方法[J]. 交通运输系统工程与信息, 2022, 22(2): 290-297.
[4]	靳志宏, 焉红, 王小寒, 邢磊, 徐奇. 滚装甩挂运输牵引车调度优化及作业模式类比分析[J]. 交通运输系统工程与信息, 2022, 22(1): 142-151.
[5]	邵斐, 张永锋, 真虹. 中国进口铁矿石海运网络抗毁性仿真[J]. 交通运输系统工程与信息, 2022, 22(1): 311-321.
[6]	彭子烜, 于滨. 内外贸同船运输下长江经济带穿梭巴士网络优化[J]. 交通运输系统工程与信息, 2022, 22(1): 322-331.
[7]	杨华龙, 赵帅奇, 方旭, 段静茹. 考虑海上意外时间和合作协议的班轮运输船期设计鲁棒优化[J]. 交通运输系统工程与信息, 2021, 21(6): 210-216.
[8]	严新平, 李晨, 刘佳仑, 游旭, 王树武, 马枫. 新一代航运系统体系架构与关键技术研究[J]. 交通运输系统工程与信息, 2021, 21(5): 22-29.
[9]	葛颖恩, 温馨. 环境可持续集装箱班轮运输管理研究综述[J]. 交通运输系统工程与信息, 2021, 21(4): 6-22.
[10]	楚金华, 李俊鹤, 王春娟, 陈超. 排放控制区下集装箱班轮航线路径规划与航速调度集成决策[J]. 交通运输系统工程与信息, 2021, 21(4): 230-238.
[11]	戈佳威, 袁克镖, 殷明, 王学锋. 传播动力学视角下集装箱海运网络关键港口节点识别[J]. 交通运输系统工程与信息, 2021, 21(4): 256-262.
[12]	戈艳艳，王姗姗. 考虑碳排放的港口全要素生产率及影响因素分析[J]. 交通运输系统工程与信息, 2021, 21(2): 22-29.
[13]	廖诗管，杨冬，白茜文，翁金贤. 基于船舶大数据的港口装卸效率值计算方法[J]. 交通运输系统工程与信息, 2021, 21(2): 217-223.
[14]	高天航，徐力，靳廉洁，葛彪. 考虑航艏向与数据变化差异的船舶轨迹预测[J]. 交通运输系统工程与信息, 2021, 21(1): 90-94.
[15]	房斯明，刘正江，封室丞，王新建. 船舶倾斜对不同行人流疏散效率影响的数值分析[J]. 交通运输系统工程与信息, 2021, 21(1): 201-206.

排放控制区下集装箱班轮运输船期设计与燃油补给联合优化

Joint Optimization of Vessel Scheduling and Refueling for Container Liner Shipping in Emission Control Areas

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics