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中国管理科学 ›› 2016, Vol. 24 ›› Issue (11): 47-57.doi: 10.16381/j.cnki.issn1003-207x.2016.11.006

• 论文 • 上一篇    下一篇

竞争环境下基于服务约束的轴-辐式海运网络优化研究

赵宇哲1,2, 周晶淼2, 匡海波1   

  1. 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
  • 收稿日期:2015-05-20 修回日期:2015-10-22 出版日期:2016-11-20 发布日期:2017-01-23
  • 作者简介: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.
  • 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

ZHAO Yu-zhe1,2, ZHOU Jing-miao2, KUANG Hai-bo1   

  1. 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:2015-05-20 Revised:2015-10-22 Online:2016-11-20 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。

关键词: 轴-辐式网络, 竞争, 服务约束, 连续化方法, 增广Lagrange乘子罚函数法

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.

Key words: hub-and-spoke network, competition, service constraints, continuous approaches, augmented Lagrange function method

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