铁路货运服务长江经济带的挑战与机遇

长江经济带货运市场竞争激烈,货源结构和消费方式快速变化,沿长江铁路货运基础设施相对薄弱等为铁路货运带来巨大挑战。长江生态优先、三峡过闸能力受限等为发展铁水联运、水运改铁运提供了重要机遇。发展铁水协同运输,吸引过闸货物及危险品运输实现"水改铁",是铁路货运服务长江经济带的重要战略选择。     

全球集装箱班轮业的变革时代

2005年10月,英国伦敦"国际化集装箱"媒体报道说,陆地运输和快件传递经营人,还有邮件公司,如德国敦豪(DHL)、Exel、TNT、美国的联合包裹(UPS)和联邦快递等等,正在转变其服务方向,将其供应链服务触角伸进了全球集装箱班轮服务业的客户群内.     

畅通国内大循环 内贸集装箱班轮"零待时"

近日,青岛海事局启动了内贸集装箱班轮信用监管新模式,与此同时公布辖区首批次入选的29艘船舶清单,后期将为信用船舶提供在港"零待时"海事服务.     

环渤海40个港口大比拼

8月31日，山东省和中国远洋运输（集团）总公司签订为期10年的战略合作框架协议，中远集团将把山东沿海港口作为集装箱班轮航线经营等方面的优先港；同一天天津南港开通试航，“双港双城”初具雏形；大连港投入建设东北区域煤炭转运和分拨中心，并谋定未来区域发展路线图。     

我国海运企业的战略选择

航运市场经营现状从1984年开始,世界前20位的集装箱班轮公司无一例外都在中国大陆设立了经营机构。面对经济全球化的要求,它们迅速扩大实力、强强联合、全球规划,以至刮起一股兼并收购的浪潮。在航运市场上,只有自身壮大,改善班轮网络,提高服务能力,才能在竞争白热化的航运市场上分一杯羹。而目前,我国海运企业中,除中远、中海等少数几家大型国有     

以合作博弈思维促班轮运输发展

经过长达几年的低各，2003年国际班轮运输市场迅速恢复、重新趋好。这集中表现为以下几个方面的特点：一是需求稳步增加，全球主干航线箱运量墙幅较大，全年运量增幅超过9％；特别是中国集装箱进出口箱量保持快速增长，可谓一枝独秀，成为全球集装箱市场增长的“风向标”     

水运

<正>首届中韩海运论坛在威海举行9月7目,由中国船东协会和山东省威海市政府共同主办的"2010中韩海运论坛"在威海举行。交通运输部副部长翁孟勇、韩国国土海洋部次官金熙国、山东省副省长才利民出席论坛开幕式并致辞。今年是中韩客货和集装箱班轮航线开通20周年,作为中韩航运企业的首届论坛,本次论坛的主题是合作与发展。     

物流

2011中国散装化学品(液体&液化气体)物流市场论坛在成功举办了七届"中国化学品运输与仓储物流论坛"的基础上,CBI易贸于6月24日在上海隆重举办国内首个专注于罐式集装箱及集装箱液袋物流市场的行业峰会——"2011中国散装化学品(液体&液化气体)物流市场论坛"。此次会议受到了国内化学品制造商&贸易商、罐箱租赁企业、罐箱运营企业、     

深圳物流业野蛮生长

<正>不到南中国,不能感受南国植物的蓬勃;不到深圳,也不能感受特区物流企业发展的效率与速度。它们有着共同的特点:迅猛发展,野蛮生长!借改革开放东风,深圳物流业书写了一段迅猛发展的传奇。1979年7月,蛇口港区在五湾开工建设深圳第一个3000吨级泊位,拉开了深圳现代物流基础设施建设和物流业的序幕。从零起步的深圳港,至2007年、2008年,集装箱吞吐量连续两年突破2000万标箱,虽然2009年受金融危机影响,箱量回落至1825万标箱,但仍牢牢占据全球集装箱港排名第四的"交椅"。目前,挂靠深圳港的国际班轮航线超过200条,覆盖了世界12大航区主要港口。深圳民航业的发展同样引人瞩目。不到二十年的时间,深圳机场已成为全国第四个客流量过2000万人次的机场和航空货运中心。依托这个航空港,顺丰物流、深圳航空等知名企业迅速壮大。     

国内水运

『两岸航商呼吁先把金马澎定为两岸航运中转地』自1997年开始集装箱班轮试点直航至今,10年间两岸共有10家航商参与两岸集装箱班轮试点直航,共运营1．56万航次,运输404 56万标箱。自2001年开始“两马”、“两门”直航至今,5年多来客运共运营1．19万航次。累计运送旅客144．08万人次；货运共运营3446航次．累计运货416．41万吨。10年来的顺利运转,已经使两岸直航成为航商和企业、民众所接受的正常流通渠道。     

从《道路交通安全法》看公路运输市场安全治理

道路运输安全是一项需综合治理的系统工程,不仅需要社会各方相互配合,更需要相应的法律手段进行规制。文章阐述了《道路交通安全法》在规范运输市场安全秩序中的作用,分析了《道路交通安全法》实施后我国公路运输市场现状及存在的问题,提出了推进道路交通运输市场规范化发展的对策建议。     

Liner container assignment model with transit-time-sensitive container shipment demand and its applications

This paper proposes a practical tactical-level liner container assignment model for liner shipping companies, in which the container shipment demand is a non-increasing function of the transit time. Given the transit-time-sensitive demand, the model aims to determine which proportion of the demand to fulfill and how to transport these containers in a liner shipping network to maximize the total profit. Although the proposed model is similar to multi-commodity network-flow (MCNF) with side constraints, unlike the MCNF with time delay constraints or reliability constraints that is NP-hard, we show that the liner container assignment model is polynomially solvable due to its weekly schedule characteristics by developing two link-based linear programing formulations. A number of practical extensions and applications are analyzed and managerial insights are discussed. The polynomially solvable liner container assignment model is then applied to address several important decision problems proposed by a global liner shipping company.     

Liner container seasonal shipping revenue management

This paper proposes a liner container seasonal shipping revenue management problem for a container shipping company. For a given weekly multi-type shipment demand pattern in a particular season, the proposed problem aims to maximize the total seasonal shipping profit by determining the number of multi-type containers to be transported and assigned on each container route, the number of containerships deployed on each ship route, and the sailing speed of containerships on each shipping leg subject to both the volume and capacity constraints of each containership. By adopting the realistic bunker consumption rate of a containership as a function of its sailing speed and payload (displacement), we develop a mixed-integer nonlinear programing with a nonconvex objective function for the proposed liner container seasonal shipping revenue management problem. A tailored branch and bound (B&B) method is designed to obtain the global ε-optimal solution of the model. Numerical experiments are finally conducted to assess the efficiency of the solution algorithm and to show the applicability of the developed model.     

Container liner fleet deployment: A systematic overview

Container liner fleet deployment (CLFD) is the assignment of containerships to port rotations (ship routes) for efficient transport of containers. As liner shipping services have fixed schedules, the ship-related operating cost is determined at the CLFD stage. This paper provides a critical review of existing mathematical models developed for the CLFD problems. It first gives a systematic overview of the fundamental assumptions used by the existing CLFD models. The operating characteristics dealt with in existing studies are then examined, including container transshipment and routing, uncertain demand, empty container repositioning, ship sailing speed optimization and ship repositioning. Finally, this paper points out four important future research opportunities: fleet deployment considering ship surveys and inspections, service dependent demand, pollutant emissions, and CLFD for shipping alliances.     

Liner ship route capacity utilization estimation with a bounded polyhedral container shipment demand pattern

This paper aims to estimate capacity utilization of a liner ship route with a bounded polyhedral container shipment demand pattern, arising in the liner container shipping industry. The proposed maximum and minimum liner ship route capacity utilization problems are formulated as a linear programming model and a min–max model, respectively. We examine two fundamental properties of the min–max model. These two nice properties enable us to develop two ε-optimal global optimization algorithms for solving the min–max model, which find a globally ε-optimal solution by iteratively cutting off the bounded polyhedral container shipment demand set with a cut. The latter algorithm overcomes non-convexity of the remaining feasible demand set generated by the former algorithm via a novel hyperplane cut. Each hyperplane cut can assure that the current vertex of the polyhedral demand set is cut off, whereas solutions that may improve the current one by more than a factor of ε are retained. Extensive numerical experiments for problems larger than those encountered in real applications demonstrate the computational efficacy of the latter algorithm.     

Game-theoretical models for competition analysis in a new emerging liner container shipping market

This paper develops three game-theoretical models to analyze shipping competition between two carriers in a new emerging liner container shipping market. The behavior of each carrier is characterized by an optimization model with the objective to maximize his payoff by setting optimal freight rate and shipping deployment (a combination of service frequency and ship capacity setting). The market share for each carrier is determined by the Logit-based discrete choice model. Three competitive game strategic interactions are further investigated, namely, Nash game, Stackelberg game and deterrence by taking account of the economies of scale of the ship capacity settings. Three corresponding competition models with discrete pure strategy are formulated as the variables in shipment deployment are indivisible and the pricing adjustment is step-wise in practice. A ɛ -approximate equilibrium and related numerical solution algorithm are proposed to analyze the effect of Nash equilibrium. Finally, the developed models are numerically evaluated by a case study. The case study shows that, with increasing container demand in the market, expanding ship capacity setting is preferable due to its low marginal cost. Furthermore, Stackelberg equilibrium is a prevailing strategy in most market situations since it makes players attain more benefits from the accommodating market. Moreover, the deterrence effects largely depend on the deterrence objective. An aggressive deterrence strategy may make potential monopolist suffer large benefit loss and an easing strategy has little deterrence effect.     

A joint optimization model for liner container cargo assignment problem using state-augmented shipping network framework

This paper proposes a state-augmented shipping (SAS) network framework to integrate various activities in liner container shipping chain, including container loading/unloading, transshipment, dwelling at visited ports, in-transit waiting and in-sea transport process. Based on the SAS network framework, we develop a chance-constrained optimization model for a joint cargo assignment problem. The model attempts to maximize the carrier’s profit by simultaneously determining optimal ship fleet capacity setting, ship route schedules and cargo allocation scheme. With a few disparities from previous studies, we take into account two differentiated container demands: deterministic contracted basis demand received from large manufacturers and uncertain spot demand collected from the spot market. The economies of scale of ship size are incorporated to examine the scaling effect of ship capacity setting in the cargo assignment problem. Meanwhile, the schedule coordination strategy is introduced to measure the in-transit waiting time and resultant storage cost. Through two numerical studies, it is demonstrated that the proposed chance-constrained joint optimization model can characterize the impact of carrier’s risk preference on decisions of the container cargo assignment. Moreover, considering the scaling effect of large ships can alleviate the concern of cargo overload rejection and consequently help carriers make more promising ship deployment schemes.     

Profit-based maritime container assignment models for liner shipping networks

We propose the problem of profit-based container assignment (P-CA), in which the container shipment demand is dependent on the freight rate, similar to the “elastic demand” in the literature on urban transportation networks. The problem involves determining the optimal freight rates, the number of containers to transport and how to transport the containers in a liner shipping network to maximize the total profit. We first consider a tactical-level P-CA with known demand functions that are estimated based on historical data and formulate it as a nonlinear optimization model. The tactical-level P-CA can be used for evaluating and improving the container liner shipping network. We then address the operational-level P-CA with unknown demand functions, which aims to design a mechanism that adjusts the freight rates to maximize the profit. A theoretically convergent trial-and-error approach, and a practical trial-and-error approach, are developed. A numerical example is reported to illustrate the application of the models and approaches.     

Reversing port rotation directions in a container liner shipping network

Reversing port rotation directions of ship routes is a practical alteration of container liner shipping networks. The port rotation directions of ship routes not only affect the transit time of containers, as has been recognized by the literature, but also the shipping capacity and transshipment cost. This paper aims to obtain the optimal port rotation directions that minimize the generalized network-wide cost including transshipment cost, slot-purchasing cost and inventory cost. A mixed-integer linear programming model is proposed for the optimal port rotation direction optimization problem and it nests a minimum cost multi-commodity network flow model. The proposed model is applied to a liner shipping network operated by a global liner shipping company. Results demonstrate that real-case instances could be efficiently solved and significant cost reductions are gained by optimization of port rotation directions.     

Strategic maritime container service design in oligopolistic markets

This paper considers the maritime container assignment problem in a market setting with two competing firms. Given a series of known, exogenous demands for service between pairs of ports, each company is free to design liner services connecting a subset of the ports and demand, subject to the size of their fleets and the potential for profit. The model is designed as a three-stage complete information game: in the first stage, the firms simultaneously invest in their fleet; in the second stage, they individually design their services and solve the route assignment problem with respect to the transport demand they expect to serve, given the fleet determined in the first stage; in the final stage, the firms compete in terms of freight rates on each origin–destination movement. The game is solved by backward induction. Numerical solutions are provided to characterize the equilibria of the game.