Terminal and yard allocation problem for a container transshipment hub with multiple terminals

This paper presents an integer programming model for the terminal and yard allocation problem in a large container transshipment hub with multiple terminals. The model integrates two decisions: terminal allocation for vessels and yard allocation for transshipment container movements within a terminal as well as between terminals. The objective function aims to minimize the total inter-terminal and intra-terminal handling costs generated by transshipment flows. To solve the problem, we develop a 2-level heuristic algorithm to obtain high quality solutions in an efficient way. Computational experiments show the effectiveness of the proposed approach.     

Tactical berth and yard template design at container transshipment terminals: A column generation based approach

Quay-side berthing congestion is an emerging challenging issue that arises in busy container transshipment terminals and calls for effective management of terminal operations. This paper tackles the berthing congestion problem by introducing a proactive management strategy from the terminal’s perspective that adjusts the calling schedule of feeder vessels in such a way that the quay-side workload distribution in the temporal dimension can be balanced. Such a schedule template design problem is considered simultaneously with another two tactical level decision problems, berth template design (i.e., determining preferred berthing positions for vessels) and yard template design (i.e., allocating storage yard space to transshipment flows). This highly integrated problem is formulated as a set covering model. Heuristic methods based on column generation are developed to obtain near-optimal solutions in an efficient way. Computational experiments on real-world sized test instances demonstrate the efficiency and effectiveness of the proposed approach.     

Determining fixed crane areas in rail–rail transshipment yards

To enable rapid container transshipment between freight trains in modern rail–rail transshipment yards efficient computerized scheduling procedures are indispensable. This paper proposes a dynamic programming approach, which determines yard areas for gantry cranes, so that the workload is evenly spread among cranes and, thus, train processing is accelerated. In a straightforward simulation of transshipment yard operations, the effect of optimal crane areas vs. equally sized areas is studied, the latter being a common real-world policy. The results indicate a remarkable speed-up of train processing if optimal crane areas are applied.     

Container storage and transshipment marine terminals

This study addresses the storage arrangement of transshipment containers on a container yard, in order to carry out efficiently the ship handling operations at a terminal where mega-containerships call. An optimization model is specified to investigate the flow of containers from the mega-containership to feeder ships using intermediate storage at the yard. A heuristic based on the lagrangian relaxation is formulated. The quality of the heuristic approach is tested in a number of experiments. In the experiments, various situations are analyzed with respect to mega-containership arrival rates, some strategies for stack arrangements and terminal layouts.     

Modeling the mixed storage strategy for quay crane double cycling in container terminals

A mixed storage strategy was proposed to improve the efficiency of yard operations and horizontal transportation to corporate with quay crane double cycling. The effects of the mixed storage strategy on terminal operations, including truck travel distance, yard crane operations and the number of required trucks, were analyzed. An approach based on cycle-time models, the queuing theory was proposed to evaluate the performances from long-term run. Results show using the mixed storage strategy, the truck travel distance can be decreased and the number of required trucks and yard crane’s operation time can be reduced by 16% and 26% respectively.     

A hybrid parallel genetic algorithm for yard crane scheduling

This paper aims at postulating a novel strategy in terms of yard crane scheduling. In this study, a dynamic scheduling model using objective programming for yard cranes is initially developed based on rolling-horizon approach. To resolve the NP-complete problem regarding the yard crane scheduling, a hybrid algorithm, which employs heuristic rules and parallel genetic algorithm (PGA), is then employed. Then a simulation model is developed for evaluating this approach. Finally, numerical experiments on a specific container terminal yard are used for system illustration. Computational results suggest that the proposed method is able to solve the problem efficiently.     

Optimal space for storage yard considering yard inventory forecasts and terminal performance

This paper presents a method for forecasting the yard inventory of container terminals over an extended period, and addresses an integrated yard planning problem for determining the optimal storage space utilization by considering the yard congestion effect on terminal performance. A formulation based on random variables and probabilistic functions was developed, which allows prediction of the storage space requirement without requiring fully-integrated simulation models. Then, an integrated cost objective function was defined. Numerical experiments were performed to illustrate how the forecasting model works and to support decision-making on yard planning and design for both inbound and outbound/transshipment areas.     

Modeling hazardous materials risks for different train make-up plans

This paper is concerned with the problem of how to place hazardous material cars in the train assembly process so that the overall derailment risk can be minimized. The approach considers both the probability of railway cars derailing en route by position as well as the risk associated with additional operations in the rail yard using recent US FRA data. The merits of this car placement model are illustrated through a case study of a railway corridor that connects Los Angeles (CA) to Chicago (IL). The case study demonstrates that the proposed risk minimization strategy could be implemented with minimal rail yard operation cost.     

Space allocating strategies for improving import yard performance at marine terminals

This paper focuses on the organization of the import storage yard at container port terminals. Three new stacking strategies are introduced which take into account the containers’ arrival and departure rates and the storage yard characteristics. A mathematical model based on probabilistic distribution functions is developed to estimate the number of rehandles required to manage an import container yard. The model is applied to the three proposed stacking strategies. Results show that the optimal strategy depends on stacking height and the relationship between vessel headway and container dwell time.     

Liner ship fleet deployment with container transshipment operations

This paper proposes a liner ship fleet deployment (LSFD) problem with container transshipment operations. The proposed problem is formulated as a mixed-integer linear programming model which allows container transshipment operations at any port, any number of times, without explicitly defining the container transshipment variables. Experiments on the Asia-Europe-Oceania shipping network of a global liner shipping company show that more than one third (17-22 ports) of the total of 46 ports have transshipment throughputs. Computational studies based on randomly generated large-scale shipping networks demonstrate that the proposed model can be solved efficiently by CPLEX.     

A heuristic algorithm for yard truck scheduling and storage allocation problems

The yard truck scheduling and the storage allocation are two important decision problems affecting the efficiency of container terminal operations. This paper proposes a novel approach that integrates these two problems into a whole. The objective is to minimize the weighted sum of total delay of requests and the total travel time of yard trucks. Due to the intractability of the proposed problem, a hybrid insertion algorithm is designed for effective problem solutions. Computational experiments are conducted to examine the key factors of the problem and the performance of the proposed heuristic algorithm.     

Container yard template planning under uncertain maritime market

A yard template determines the assignment of spaces in a yard for arriving vessels. Fluctuation of demand for freight transportation brings new challenges for making a robust yard template when facing uncertain maritime market. A model is proposed for yard template planning considering random numbers of containers that will be loaded onto vessels that visit the port periodically. Traffic congestions and multiple schedule cycle times for vessel arrival patterns are also considered. Moreover, a meta-heuristic method is developed for solving the model in large-scale cases. Numerical experiments are conducted to validate effectiveness and efficiency of the model.     

Sailing speed optimization for container ships in a liner shipping network

This paper first calibrates the bunker consumption - sailing speed relation for container ships using historical operating data from a global liner shipping company. It proceeds to investigate the optimal sailing speed of container ships on each leg of each ship route in a liner shipping network while considering transshipment and container routing. This problem is formulated as a mixed-integer nonlinear programming model. In view of the convexity, non-negativity, and univariate properties of the bunker consumption function, an efficient outer-approximation method is proposed to obtain an ε-optimal solution with a predetermined optimality tolerance level ε. The proposed model and algorithm is applied to a real case study for a global liner shipping company.     

Fulfillment source allocation,inventory transshipment,and customer order transfer in e-tailing

We consider an inventory fulfillment-allocation and transshipment problem in an e-tailing environment. For a typical e-tailer, each customer demand is fulfilled from the closest fulfillment center if there are enough inventories. Otherwise, the e-tailer would transship stock from a nearby facility or transfer the customer order so it is fulfilled from another facility, depending on the economics of transportation. We develop a mixed-integer programming model to help e-tailers optimally fulfill customer orders while minimizing logistics costs. We propose a Benders decomposition-based approach to efficiently find optimal solutions. Our computational results demonstrate the importance of considering inventory transshipments in online deliveries.     

Optimizing the block size in container yards

A block is the basic unit of storage space in container terminals. This study proposes two methods for optimizing the block size, by considering the throughput requirements of yard cranes (YCs) and the block storage requirements. To estimate the YC performance, cycle-time models of various handling operations of YCs are analytically derived. Two types of container yards are examined: those with blocks that are laid out parallel to the quay and those laid out vertical to the quay.     

Intermodal routing of Canada–Mexico shipments under NAFTA

This paper obtains the optimal routings for intermodal containerized transport from Canada to Mexico. Such traffic is being stimulated by the North American Free Trade Agreement (NAFTA), but the cost and lead times of feasible routes are not well known. We summarize the links and routes to Mexico on which one or more carriers now operate, and then determine non-dominated tradeoffs between cost and service. Every southbound route from Canada requires a transshipment point in the southern or southwestern U. S. Feasible transshipment points are also candidate locations for a manufacturing ‘twin plant’, a distribution centre, or a transportation hub. Here, as a first step in this bigger problem, a network is constructed between five Canadian origins and three important Mexican destinations. Each link employs available intermodal services whose transit time and transportation cost are obtained through industry sources. A shortest-path algorithm enables calculation of the route requiring least time and the route of minimum cost. Non-dominated time/cost tradeoffs are identified for each origin–destination pair. After including inventory expenses (by parametrizing the unit value of lead time), total-cost curves then eliminate some routing alternatives. Guidelines are provided on the effects of mode, carrier, and O–D locations on selection of intermodal routes to Mexico. Finally, two new intermodal services are proposed and their benefits discussed.     

The application of inventory transshipment modeling to air cargo revenue management

This paper applies an inventory transshipment modeling approach to investigate the air cargo revenue management problem for an airline operating in a two-segment network. Building upon an extension of the classic two-location inventory transshipment model, we develop a framework to optimize an airline’s cargo overbooking decisions in a two-segment network setting. We find consistent evidence indicating that network-based global optimization always leads to greater expected profits than does local (i.e., market by market) optimization. Further, the magnitude of profit improvement is found to be most significant when local shipments have a relatively higher freight yield compared to flow-through shipments. Finally, our results indicate that global optimization contributes to greater profit improvement as offloading penalty costs become higher.     

Path to a multilayered transshipment port system: How the Yangtze River bulk port system has evolved

China's steel output has maintained rapid growth over the past twenty years. Due to this, a large number of iron ore ports/terminals have been built along the Yangtze River, and the Yangtze River bulk port system has experienced a unique development in its structure. This paper aims to understand the evolution of this bulk port system.¹ along the Yangtze River. To achieve this objective, first the development phases of the Yangtze River bulk port system are reviewed, taking the theoretical (container) port evolution model as a benchmark. Then several hypotheses addressing certain features of bulk port system development are proposed, followed by using panel data analysis to test these hypotheses. Based on this discussion and analysis, the major driving forces that are reshaping bulk port development along the Yangtze River are then summarized. It is found that evolution of the Yangtze River bulk port system in general follows the port development models in previous literature. However, the trend toward regionalization and an offshore hub have not appeared. Besides this, iron ore transshipment is moving outward both for sea ports and river ports, and few iron ore transshipment gateway hubs are occurring. Furthermore, the transshipment function of a bulk port plays a significant role in port traffic changes, but this role is affecting sea ports differently to river ports. The container throughput of transshipment sea ports has a significant negative effect on bulk traffic, whereas that of transshipment river ports has a positive effect. Geographical conditions, institutional factors and national policy, industry agglomeration, changes in market supply and demand, and technology updates are major factors driving changes to the port system structure. These factors are observed to function either individually or collectively at different development stages.     

European intermodal freight transport network: Market structure analysis

The analysis of market structure and concentration measures for the Intermodal Freight Transport (IFT) market is important to avoid market failure and to find the areas for policy making to promote IFT market share. This analysis can be performed for separate segments, for example, the market for transshipment service or the market for main-haulage service. However, due to the multistage characteristic of IFT service, the segmental analysis gives an incomplete view of the IFT market at the network level. In a previous paper (Saeedi et al., 2017), we present the Intermodal Freight Transport Market Structure (IFTMS) model to conduct a network-based study of the IFTMS in which distinctive actors (i.e., pre/post haulage operators, terminals, rail/barge operators, transport chains, and corridors) are competing at different levels inside distinctive markets to deliver an integrated IFT service. There are two main challenges in the application of IFTMS model in real cases, for example, the European IFT network. First, the definition of the geographical and spatial border of the transshipment market areas is needed to determine which actors are potentially competing for a specific service demand. The second challenge is the lack of disaggregated data and the consistency of existing data in nodes (i.e., the transshipment areas) and links (i.e., the rail and barge operators). To cope with these challenges, we develop a four-step methodology in which a model-based approach is used to define the geographic boundaries of the transshipment submarkets and provide detailed and consistent data for market analysis. We also apply the IFTMS model to study the market structure of European intermodal network. Our analysis shows that the majority of transshipment markets as well as main-haulage markets are highly concentrated markets. The corridor markets – which include the IFT chains – are unconcentrated markets. Furthermore, the majority of corridors in the European Union are inside highly concentrated origin-destination markets.     

横列联设企业调车场能力计算方法

中小型企业调车场通常采用横列联设布置。这种调车场的能力计算,可先根据调机和车辆在调车场内的作业流程和走行径路,建立各项作业占用调车场的时间计算公式。然后通过调整企业调车场运输量的大小,计算其能力利用率,采用逐步逼近的方法,试算出能力达到100%时的相应运输量,确定企业调车场的能力。并以某钢铁公司企业调车场为例具体说明其计算过程。