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竞争环境下基于服务约束的轴-辐式海运网络优化研究

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  • 1. 大连海事大学综合交通运输协同创新中心, 辽宁 大连 116026;
    2. 大连理工大学管理与经济学部, 辽宁 大连 116023
赵宇哲(1983-),男(汉族),黑龙江大庆人,大连海事大学交通运输管理学院,副教授,博士,研究方向:海运网络优化、港口绿色增长,Email:zhaoyuzhe@126.com.

收稿日期: 2015-05-20

  修回日期: 2015-10-22

  网络出版日期: 2017-01-23

基金资助

国家自然科学基金资助项目(71403035,71273037);教育部“创新团队发展计划”项目(IRT13048);辽宁省自然科学基金(2015020080);中国博士后科学基金面上资助项目(2016MS90227);辽宁省经济社会发展课题重点资助项目(2017lslktzd-004);辽宁省高等教育有内涵发展专项资金资助项目(20110116103)

The Hub-and-spoke Shipping Network Optimization with Service Constraints in a Competitive Environment

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  • 1. Collaborative Innovation Center for Transport Stndies, Dalian Maritime University, Dalian 116026, China;
    2. Faculty of Management and Economics, Dalian University of Technology, Dalian 116023, China

Received date: 2015-05-20

  Revised date: 2015-10-22

  Online published: 2017-01-23

摘要

针对同一海运市场中不同的海运企业——领导者与跟随者在设计多分配的轴-辐式海运网络时引起的竞争问题,突破已往枢纽港口集合是给定的假设,将航线连接设计扩展为可存在多条,引入基于服务约束(服务质量\价格\时间)的吸引力模型来定量表示托运人的选择行为,建立了竞争环境下基于服务约束的轴-辐式海运网络优化问题的数学模型,利用NCP函数、凝聚函数和增广Lagrange乘子罚函数法对这一问题进行求解。算例仿真结果显示:(1)跟随者在托运人考虑单位服务价格时,即使不存在规模经济效应,跟随者也可通过建立合适的枢纽港口来获取一定的市场机会;(2)跟随者在存在较大规模经济效应时其利润最可观,因采用比例模型,在不存在规模经济效应下跟随者在领导者决定设计不同数量的枢纽港口时其利润不会统一收敛于某一定值;(3)跟随者在领导者仅设计1个枢纽港口时可通过建立大量的枢纽港口来争夺丰厚的利润,但对于港口集合 N={1,2,…,12} 的海运市场,领导者只需设计2个以上枢纽港口时跟随者的利润空间便会受到较大挤压。

本文引用格式

赵宇哲, 周晶淼, 匡海波 . 竞争环境下基于服务约束的轴-辐式海运网络优化研究[J]. 中国管理科学, 2016 , 24(11) : 47 -57 . DOI: 10.16381/j.cnki.issn1003-207x.2016.11.006

Abstract

The current trend of global trade enhance the importance of shipping service, since it is in charge of transporting up to 90% of the trade volume. Recently, a number of shipping alliances have emerged to dominate the shipping market, and most of the smaller shipping companies are suffering from an ongoing loss of their profits. It is therefore essential for the smaller shipping companies-that are not operating in shipping alliances to seek for ways of competing with the shipping alliances in order to achieve some higher profits or at least to recover the lost market shares. An integer nonlinear programming model is propesed for the hub-and-spoke shipping network optimization with service constraints in a competitive environment to address the considered problem. An existing shipping alliance, called the leader, utilizes a transportation network with a multi-allocation hub-and-spoke topology. A new shipping company, the follower, wants to offer its shipping service in the same shipping market, using its own multi-allocation hub-and-spoke shipping network and setting service quality, service time and service cost so as to maximize its profits. The question to be answered is: Can the follower obtain profits under these conditions, even with same service quality, service time and service cost ofthe leader? In order to answer this question, our procedure finds how many hub ports to locate, where should they be located, what is the best route network. The contributions of this paper are as follows. In the first place, continuous hub location model (the domain of hub ports is a plane not a series of particular ports) is formulated. Secondly, the numbers of routes existing in the origin-destination ports are extended. Third, an attraction function which is a proportional model not a discrete choice model is provided to simulate the consignors' choice behavior. Finally, the integer nonlinear problem is solved using an augmented Lagrange function method based on NCP function and coagulation function. Consequently, the conclusions are achieved by example simulation that, (1) the follower will obtain certain profits by opening moderate number of hub ports in the case of service cost is considered by consignors (θ>0), even if there is no economies of scale =1.0); (2) the follower's benefits will be the most significant if there are high economies of scale (α=0.2), but its profits in the case of the leader has different amount of hub ports (PA) located will not unified converges to a certain value if there is no economies of scale (α=1.0) by the fact of a proportional model is applied; (3) the follower can obtain much profits by opening more hub ports if the leader has one hub ports (PA=1), but its capability of obtaining a higher profits will be reducing if the leader has operated more than two hub ports (PA>2) for the 12-node versionof the shipping network.

参考文献

[1] Held D, McGrew A G,Goldblatt D, et al.Global transformations: Politics, economics and culture[M]. Basingstoke, UK:Macmillan in association with Political Studies Association, 2000.

[2] Asgari N, Farahani R Z, Goh M. Network design approach for hub ports-shipping companies competition and cooperation[J]. Transportation Research Part A:Ploicy and Practice, 2013, 48: 1-18.

[3] Munari P F. Competition in liner shipping[M].Berlin Heldelbery:Springer, 2012.

[4] 王成金. 集装箱港口网络形成演化与发展机制[M]. 科学出版社, 2012.

[5] Ducruet C, Notteboom T. The worldwide maritime network of container shipping: Spatial structure and regional dynamics[J]. Global networks, 2012, 12(3): 395-423.

[6] Zheng Jianfeng, Meng Qiang, Sun Zhuo. Liner hub-and-spoke shipping network design[J]. Transportation Research Part E: Logistics and Transportation Review, 2015, 75(3): 32-48.

[7] 李阳. 轴-辐式网络理论及应用研究[D]. 上海: 复旦大学, 2006.

[8] Campbell J F, O'Kelly M E. Twenty-five years of hub location research[J]. Transportation Science, 2012, 46(2): 153-169.

[9] Alumur S, Kara B Y. Network hub location problems: The state of the art[J]. European Journal of Operational Research, 2008, 190(1): 1-21.

[10] Klincewicz J G. Hub location in backbone/tributary network design: A review[J]. Location Science, 1998, 6(1): 307-335.

[11] Faharani R Z, Hetmakfar M, Arabani A B,et al. Hub location problems: A review of models, classification, solution techniques, and applications[J]. Computers and Industrial Engineering, 2013, 64(4): 1096-1109.

[12] Marianov V, Serra D, ReVelle C. Location of hubs in a competitive environment[J]. European Journal of Operational Research, 1999, 114(2): 363-371.

[13] Gelareh S, Nickel S, Pisinger D. Liner shipping hub network design ina competitive environment[J]. Transportation Research Part E: Logistics and Transportation Review, 2010, 46(6): 991-1004.

[14] 赵宇哲. 竞争环境下的轴-辐式集装箱海运网络设计问题[J]. 中国管理科学, 2015, 23(7):103-112.

[15] 陈康, 郭利泉, 杨忠振. 基于混合航线结构的集装箱航线与空重箱运输综合优化模型[J]. 系统工程理论与实践, 2014, 34(1):122-128.

[16] Zheng Jianfeng, Meng Qiang, Sun Zhuo. Impact analysis of maritime cabotage legislations on liner hub-and-spoke shipping network design[J]. European Journal of Operational Research, 2014, 234(3): 874-884.

[17] 赵宇哲, 段浩, 张连如. 不确定OD需求下的轴-辐式集装箱海运网络设计[J]. 系统工程, 2014, 32(4):21-29.

[18] Reilly W J. The law of retail gravitation[M]. New York: Knickerbocker Press,1931.

[19] Huff D L. Defining and estimating a trading area[J]. Journal of Marketing 1964, 28(3):34-38.

[20] Eiselt H A, Marianov V. A conditional p-hub location problem with attraction functions[J]. Computers and Operations Research, 2009, 36(12): 3128-3135.

[21] Ortúzar J D, Willumsen L G. Modelling transport[M]. WestSussex, UK: Wiley-Blackwell, 2011.

[22] 李进, 傅培华, 李修琳,等. 低碳环境下的车辆路径问题及禁忌搜索算法研究[J]. 中国管理科学, 2015, 23(10):98-106.

[23] 方健, 徐丽群. 随机需求下考虑碳排放的供应商选择问题研究[J]. 中国管理科学, 2016, 24(2): 56-60.

[24] Li X Singsi. An aggregate constraint method for non-linear programming[J]. Journal of the Operational Research Society, 1991, 42(11):67-110.

[25] 杨庆之. 对凝聚函数法的分析[J]. 计算数学, 1996, 11(4):405-410.

[26] 袁亚湘. 非线性优化计算方法[M]. 北京: 科学出版社, 2008.
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