时间敏感型货物两阶段集装箱舱位分配问题研究

doi:10.12005/orms.2018.0223

摘要/Abstract

摘要： 本文旨在探索如何对时间敏感型货物的集装箱舱位分配和动态定价问题进行研究。考虑到时间敏感型货物对配送时间的要求,本文提出一种新的定价机制,即在该类货物的运费制定时,考虑时间敏感型货物的配送时效及港口拥挤对其存在的影响,建立运价和配送时间之间的关系。另外,以船舶公司总运费收益最大化为目标,构建两阶段随机整数规划模型,运用机会约束规划方法对模型进行求解。最后,通过算例研究,验证了模型及算法的有效性。结果表明,本文针对时间敏感型货物所提出的定价机制能够显著提高船公司收益。

关键词: 集装箱舱位分配, 时间敏感型货物, 港口拥挤, 两阶段, 动态定价

Abstract: In this paper we explore how to allocate container slots with dynamic pricing for time-sensitive cargo. Given the specific requirement of time-sensitive cargo to delivery time, a new pricing pattern is proposed, in which we take the time limit of time-sensitive cargo and port congestion into consideration, and make a correlation between freight charge and delivery time when determining cargo’s freight. This paper develops a two-phase stochastic integer programming model (2PSIPM) to maximize the revenue of shipping company. The solution algorithms are proposed as well, in which chance constrained programming (CCP) method is introduced to solve the model. Finally, a numerical example is presented to test the applicability of the proposed model and solution algorithms, and the result indicates that the proposed pricing pattern for time-sensitive cargo can significantly increase the revenue of a shipping company.

Key words: container slot allocation, time-sensitive cargo, port congestion, two-phase, dynamic pricing

中图分类号:

U169.1

汪挺松, 李曼. 时间敏感型货物两阶段集装箱舱位分配问题研究[J]. 运筹与管理, 2018, 27(10): 1-10.

WANG Ting-song, LI Man. Two-phase Container Slot Allocation for Time-sensitive Cargo[J]. Operations Research and Management Science, 2018, 27(10): 1-10.

参考文献

[1]Yang D, Ong G P, Chin A T H. An exploratory study on the effect of trade data aggregation on international freight mode choice[J]. Maritime Policy & Management, 2014, 41(3):212-223.
[2]UNCTAD. Review of maritime transportation: paper presented at the united nations conference on trade and development[R]. New York and Geneva, 2016. http://unctad.org/en/Publications Library/rmt 2016_en.pdf.
[3]董毓芬,何平,徐晓燕.时间价格敏感型需求下的二阶段供应链协调模型[J].中国管理科学,2011,19(4):93-97.
[4]陈秋双,杜玉泉,徐亚.不确定环境下集装箱码头的扰动管理[J].物流技术,2010,29(2):1-5.
[5]Brooks M R, Schellinck T. Measuring port effectiveness: what really determines cargo interests’ evaluations of port service delivery?[J]. Maritime Policy & Management, 2015, 42(7):699-711.
[6]Wan Y, Yuen C L, Zhang A. Effects of hinterland accessibility on US container port efficiency[J]. International Journal of Shipping & Transport Logistics, 2014, 6(4):422-440.
[7]Shang X T, Cao J X, Ren J. A robust optimization approach to the integrated berth allocation and quay crane assignment problem[J]. Transportation Research Part E Logistics & Transportation Review, 2016, 94:44-65.
[8]Jiang C, Wan Y, Zhang A. Internalization of port congestion: strategic effect behind shipping line delays and implications for terminal charges and investment[J]. Social Science Electronic Publishing, 2017:1-19.
[9]Maragos S A. Yield management for the maritime industry[D]. Massachusetts Institute of Technology, 1994.
[10]Feng C, Chang C. Empty container reposition planning for intra-asia liner shipping[J]. Maritime Policy & Management, 2008, 35 (5):469-489.
[11]Song D, Carter J. Empty container repositioning in liner shipping[J]. Maritime Policy & Management, 2009, 36 (4):291-307.
[12]Feng C M, Chang C H. Optimal slot allocation with empty container reposition problem for Asia ocean carriers[J]. International Journal of Shipping and Transport Logistics, 2010, 2 (1):22-43.
[13]Bu X Z, Zhao Q W, Huang Q, et al. Optimal capacity allocation model of ocean shipping container revenue management considering empty container transportation[J]. Chinese Journal of Management Science, 2005, 13(1):71-75.
[14]Wang X. Stochastic resource allocation for containerized cargo transportation networks when capacities are uncertain[J]. Transportation Research Part E: Logistics & Transportation Review, 2016, 93:334-357.
[15]Liu D, Yang H. Joint slot allocation and dynamic pricing of container sea-rail multimodal transportation[J]. Journal of Traffic and Transportation Engineering (English Edition), 2015, 2(3):198-208.
[16]李冰州,陈旭,武振业.基于收益管理的海运集装箱舱位定价与分配[J].系统工程,2005,23(12):69-73.
[17]卜祥智,赵辉,武振业,黄庆. 基于收益管理的海运集装箱舱位分配随机规划模型[J].系统工程理论方法应用,2005,14(4):330-334.
[18]卜祥智,赵泉午,陈荣秋.基于收益管理的海运集装箱舱位分配与路径选择优化模型[J].管理工程学报, 2008,22(3):94-99.
[19]杨华龙,刘迪,王霞, 张燕.集装箱班轮运输两阶段舱位分配与动态定价模型[J].系统工程理论与实践, 2012,32(12):2684-2691.
[20]Panayides P, Song D. Maritime logistics as an emerging discipline[J]. Maritime Policy & Management, 2013, 40(3):295-308.
[21]Wang S, Meng Q. Liner shipping network design with deadlines[J]. Computers and Operations Research, 2014, 41:140-149.
[22]Meng Q, Wang S. Optimal operating strategy for a long-haul liner service route[J]. European Journal of Operation Research, 2011, 215(1):105-114.
[23]Wang S, Meng Q, Sun Z. Container routing in liner shipping[J]. Transportation Research Part E: Logistics & Transportation Review, 2013, 49 (1):1-7.
[24]Meng Q, Wang T, Wang S. Multi-period liner ship fleet planning with dependent uncertain container shipment demand[J]. Maritime Policy & Management, 2015, 42 (1):43-67.
[25]Wang S, Meng Q. Robust schedule design for liner shipping services[J]. Transportation Research Part E: Logistics & Transportation Review, 2012, 48 (6):1093-1106.
[26]Wang S, Alharbi A, Davy P. Liner ship route schedule design with port time windows[J]. Transportation Research Part C: Emerging Technol. 2014, 41:1-17.
[27]Meng Q, Wang S, Andersson H, et al. Containership Routing and Scheduling in Liner Shipping: Overview and Future Research Directions[J]. Transportation Science, 2014, 48(2):265-280.
[28]Wang S,Meng Q,Liu Z.Containership scheduling with transit-time-sensitive container shipment demand[J].Transportation Research Part B Methodological,2013,54(3):68-83.
[29]Wang S, Meng Q, Lee C Y. Liner container assignment model with transit-time-sensitive container shipment demand and its applications[J]. Transportation Research Part B, 2016, 90:135-155.
[30]Wang T, Meng Q, Wang S, et al. Risk management in liner ship fleet deployment: A joint chance constrained programming model[J]. Transportation Research Part E Logistics & Transportation Review, 2013, 60(4):1-12.
[31]Charnes A, Cooper W W. Chance-constrained programming[J]. Management Science, 1959, 6 (1):73-79.
[32]Kamath K R, Pakkal T P M. A Bayesian approach to a dynamic inventory model under an unknown demand distribution[J]. Computers & Operations Research, 2002, 29(4):403-422.
[33]Wallace S W, Fleten S E. Stochastic Programming Models in Energy[J]. Handbooks in Operations Research & Management Science, 2003, 10:637-677.