The container retrieval problem with respect to relocation

The demand for container terminal yards is growing significantly faster than the supply of available land; therefore, containers are typically stacked high to better utilize the land space in container yards. However, in the process of container retrieval, non-productive reshuffling may be required to relocate the containers that are stacked on top of the target container. Container retrieval is directly related to the operational efficiency of terminals. Because the industry has become increasingly competitive, it has become critical to introduce a systematic approach to retrieving containers. In this study, we develop a heuristic that can generate feasible working plans for rail-mounted gantry cranes (RMGC) in container yards to minimize the number of container movements while taking the RMGC working time into consideration. The methodology takes into consideration the case that containers are grouped in terms of their retrieval order. Multi-lift RMGC models also are studied. Comprehensive numerical experiments reveal that the method runs faster than other methods published in the literature by several orders of magnitude; additionally, our method is able to solve instances larger than practical use. The number of movements approaches a theoretical lower bound, and the numerical results clearly demonstrate the tradeoff between the number of movements and the working time, and provide useful insights for yard planning.     

Storage space allocation in container terminals

Container terminals are essential intermodal interfaces in the global transportation network. Efficient container handling at terminals is important in reducing transportation costs and keeping shipping schedules. In this paper, we study the storage space allocation problem in the storage yards of terminals. This problem is related to all the resources in terminal operations, including quay cranes, yard cranes, storage space, and internal trucks. We solve the problem using a rolling-horizon approach. For each planning horizon, the problem is decomposed into two levels and each level is formulated as a mathematical programming model. At the first level, the total number of containers to be placed in each storage block in each time period of the planning horizon is set to balance two types of workloads among blocks. The second level determines the number of containers associated with each vessel that constitutes the total number of containers in each block in each period, in order to minimize the total distance to transport the containers between their storage blocks and the vessel berthing locations. Numerical runs show that with short computation time the method significantly reduces the workload imbalance in the yard, avoiding possible bottlenecks in terminal operations.     

Bi-objective optimization for the container terminal integrated planning

In this paper, we study the joint optimization of the tactical berth allocation and the tactical yard allocation in container terminals, which typically consist of berth side and yard side operations. The studied two objectives are: (i) the minimization of the violation of the vessels’ expected turnaround time windows with the purpose of meeting the timetables published by shipping liners, and (ii) the minimization of the total yard transportation distance with the aim to lower terminal operational cost. We propose a bi-objective integer program which can comprehensively address the import, export and transshipment tasks in port daily practice. Traditionally, a container transshipment task is performed as a couple of import and export tasks, called indirect-transshipment mode, in which the transit container are needed to be temporally stored in the yard. As the way of transferring containers directly from the incoming vessel to the outgoing vessel, called direct-transshipment mode, has potential to save yard storage resources, the proposed model also incorporates both indirect- and direct-transshipment modes. To produce Pareto solutions efficiently, we devise heuristic approaches. Numerical experiments have been conducted to demonstrate the efficiency of the approaches.     

Comparative evaluation of resource cycle strategies on operating and environmental impact in container terminals

This paper examines the use of single and dual cycle operations for three types of resources, namely, quay cranes, vehicles, and yard cranes to improve the operating efficiency and reduce the energy consumption in a container terminal. Various cycle strategies are proposed and their corresponding estimation models, describing the stowage distributions of outbound and inbound containers on a ship and the storage sharing level of blocks in the yard, are formulated to estimate the total number of cycles for the resources. Statistical analyses are conducted to evaluate and compare the effect of different cycle strategies on the cycle reductions. From the experiment results, it was found that collaboration between resources with the single cycle operation always outperforms that under the dual cycle operation without collaboration.     

Effects of demurrage and detention regimes on dry-port-based inland container transport

Increase of congestion at container deep seaports and shortage of capacity has led inland transport systems worldwide to rely more and more on inland terminals, and on the use of high capacity modes of transport to generate economies of scale and reduce negative effects of trucking. In this setting, planning the transport of maritime containers between a deep seaport and a final inland destination must also consider due dates and soft time windows, the latter known as Demurrage and Detention (D&D). In this paper, we formalize the concept of D&D, model the multimodal planning problem, and assess the impact of different D&D regimes on the emerging inland transport systems. By means of an experimental framework, we compare different D&D policies and provide managerial insights. The experiments highlight the effects of existing D&D regimes on transport efficiency and provide guidelines for their choice in practice. D&D are shown to have a twofold effect: first to limit consolidation opportunities and force the use of trucks as buffer, and second to push containers to dwell unnecessarily at the seaports.     

Gantry crane operations to transfer containers between trains: A simulation study of a Spanish terminal

Freight transfer operations are critical in combined transport networks. In this paper a simulation model and modelling approach to the transfer of cargo between trains at rail terminals is presented. The model is used to study the Port-Bou terminal, the main intermodal terminal at the Spanish-French frontier. Four different gantry crane operation modes to interchange containers between trains are evaluated. These operation rules are tested in several scenarios to examine the critical factors of the system and the best operation rule for each situation. Latest generation software is used to develop the model that incorporates modular programming and enhanced graphic systems for output representation. It allows a dynamic display of the simulated system and, likewise, the possibility of developing modules that can be reused in other studies. The research shows how simulation can be a useful planning tool in the rail transportation context.     

Green vehicle technology to enhance the performance of a European port: A simulation model with a cost-benefit approach

In this paper, we study the impact of using a new intelligent vehicle technology on the performance and total cost of a European port, in comparison with existing vehicle systems like trucks. Intelligent autonomous vehicles (IAVs) are a new type of automated guided vehicles (AGVs) with better maneuverability and a special ability to pick up/drop off containers by themselves. To identify the most economical fleet size for each type of vehicle to satisfy the port’s performance target, and also to compare their impact on the performance/cost of container terminals, we developed a discrete-event simulation model to simulate all port activities in micro-level (low-level) details. We also developed a cost model to investigate the present values of using two types of vehicle, given the identified fleet size. Results of using the different types of vehicles are then compared based on the given performance measures such as the quay crane net moves per hour and average total discharging/loading time at berth. Besides successfully identifying the optimal fleet size for each type of vehicle, simulation results reveal two findings: first, even when not utilising their ability to pick up/drop off containers, the IAVs still have similar efficacy to regular trucks thanks to their better maneuverability. Second, enabling IAVs’ ability to pick up/drop off containers significantly improves the port performance. Given the best configuration and fleet size as identified by the simulation, we use the developed cost model to estimate the total cost needed for each type of vehicle to meet the performance target. Finally, we study the performance of the case study port with advanced real-time vehicle dispatching/scheduling and container placement strategies. This study reveals that the case study port can greatly benefit from upgrading its current vehicle dispatching/scheduling strategy to a more advanced one.     

Dynamic blocking for railyards: Part I. Homogeneous traffic

This paper and its companion present a study of railroad classification yard strategies that allow for blocks of destinations to be assigned to classification tracks in different ways, depending on the time of day, week or month. With the same number of tracks, more classifications can be handled by this method. The paper examines homogeneous traffic; that is, traffic patterns where all blocks have the same amount of traffic, where cars for all blocks depart equally frequently from the yard and where the overall traffic flow does not change with time. The results represent the beginning of a better understanding of yard operations, which should be useful for designing new yards, planning expansions of existing ones and evaluating the impact of changes (planned and unplanned) on traffic patterns. The paper concentrates on two sorting strategies: sorting by train (perhaps the most commonly used strategy in the United States today), and triangular sorting. For both strategies, formulas are given for the minimum number of tracks, number of switches and for the total space requirements. For triangular sorting, the yard delay and total space depend on the time chosen between reswitches. These two measures of performance can be reduced if one is willing to accept a sorting effort slightly higher than minimum. The trade-off can be explored numerically. For sorting by train, yard delay and total space are not significantly affected by the sorting method; there is no such trade-off. It appears that sorting by train results in less work, delay and space requirements than triangular sorting, at least in most instances when either could be used. Triangular sorting, however, can be used when there are not enough tracks to allow sorting by train.     

Modeling of yard congestion and optimization of yard template in container ports

As a tactical-level plan, a yard template determines the assignment of spaces in a container port yard for arriving vessels. This paper investigates the concept of yard congestion quantitatively in the context of yard truck interruptions, and develops a combination of probabilistic and physics-based models for truck interruptions. The above work enables us to exactly evaluate the expected link travel time, which then acts as the basis for proposing a mixed-integer programming model that minimizes the total expected travel time of moving containers around the yard. A Squeaky Wheel Optimization based meta-heuristic is developed to solve the model. Experiments are also conducted to validate the effectiveness of the model and the solution method.     

A tabu search algorithm to solve the integrated planning of container on an inter-terminal network connected with a hinterland rail network

Transport demand for containers has been increasing for decades, which places pressure on road transport. As a result, rail transport is stimulated to provide better intermodal freight transport services. This paper investigates mathematical models for the planning of container movements in a port area, integrating the inter-terminal transport of containers (ITT, within the port area) with the rail freight formation and transport process (towards the hinterland). An integer linear programming model is used to formulate the container transport across operations at container terminals, the network interconnecting them, railway yards and the railway networks towards the hinterland. A tabu search algorithm is proposed to solve the problem. The practical applicability of the algorithm is tested in a realistic infrastructure case and different demand scenarios. Our results show the degree by which internal (ITT) and external (hinterland) transport processes interact, and the potential for improvement of overall operations when the integrated optimization proposed is used. Instead, if the planning of containers in the ITT system is optimized as a stand-alone problem, the railway terminals may suffer from longer delay times or additional train cancellations. When planning the transport of 4060 TEU containers within one day, the benefits of the ITT planning without considering railway operations account for 17% ITT cost reduction but 93% railway operational cost growth, while the benefits of integrating ITT and railway account for a reduction of 20% in ITT cost and 44% in railway operational costs.     

Automated guided vehicle system for two container yard layouts

The explosive growth in the freight volumes has put a lot of pressure on seaport authorities to find better ways of doing daily operations in order to improve the performance and to cope with avalanches of containers processing at container terminals. Advanced technologies, and in particular automated guided vehicle systems (AGVS), have been recently proposed as possible candidates for improving the terminal’s efficiency not only due to their abilities of significantly improving the performance but also to the repetitive nature of operations in container terminals. The deployment of AGVS may not be as effective as expected if the container terminal suffers from a poor layout. In this paper, simulation models are developed and used to demonstrate the impact of automation and terminal layout on terminal performance. In particular, two terminals with different but commonly used yard configurations are considered for automation using AGVS. A multi attribute decision making (MADM) method is used to assess the performance of the two terminals and determine the optimal number of deployed automated guided vehicles (AGVs) in each terminal. The simulation results demonstrate that substantial performance can be gained using AGVS. Furthermore, the yard layout has an effect on the number of AGVs used and on performance.     

Performance analysis of cargo-handling equipment from a green container terminal perspective

This study employs a green container terminal perspective to compare the performance of four types of cargo handling equipment used in container yards – automatic rail, rail, electric tire, and tire transtainers – based on working efficiency, energy saving performance, and carbon reductions. It is found that automatic rail and electric tire transtainers are the optimal types of green cargo handling equipment.     

Cranes scheduling in frame bridges based automated container terminals

This paper investigates crane scheduling problems for a new type of automated container terminal system, which is based on multi-storey frame bridges. For the new design concept, this paper studies how to schedule two types of cranes, i.e., quay cranes and bridge cranes that transfer containers between different storeys. The schedules of these two types of cranes impact the operation efficiency of the terminal system. Mathematical models are proposed for the two scheduling problems. Meta-heuristics are developed to solve them. Numerical experiments are conducted to validate the effectiveness of the proposed models and the efficiency of the proposed solution method.     

Railroad classification yard throughput: The case of multistage triangular sorting

Procedures for improving the efficiency of classification yard operations are studied in this paper. Multistage sorting strategies make efficient use of land and tracks. Equations are derived giving the service time per car and space requirements of three multistage sorting strategies: the sorting-by-block, the sorting-by-train, and the triangular sorting strategies. Exact service time formulas are given for the first two strategies, and an approximation is given for the last strategy. The approximation, when compared with exact calculations, proved to be quite robust. Errors were on the order of one percent. Sensitivity analysis showed that the formulas are accurate when assumptions used in the approximations are not satisfied. A surprising finding was that the triangular sorting strategy, which allows many more classifications on a given set of tracks than the other two, does not require significantly greater service time in flat yards. Presently, the triangular strategy is not widely used in the U.S., in preference for the sorting-by-block strategy.     

大型贝雷主梁龙门吊的结构设计与拼装

针对飞龙岛大桥钢箱梁的长距离吊运与安装实际,文章设计出承重标准值200 t的贝雷主梁钢管支腿龙门吊,并通过有限元模拟分析及稳定性验算,对龙门吊主体结构杆系的反力、应力、挠度及稳定性进行分析。同时,文章阐述了龙门吊主体结构的拼装工艺,为大吨位贝雷片主梁龙门吊设计与拼装提供了依据。     

Multi-period yard template planning in container terminals

This paper is about yard management in container ports. As a tactical level decision-making tool in a port, a yard template determines the assignment of spaces (subblocks) in a yard for arriving vessels, which visit the port periodically. The objective of yard template planning is to minimize the transportation cost of moving containers around the yard. To handle yard template planning, a mixed integer programming model is proposed that also takes into account traffic congestion in the yard. A further complication is that the cycle time of the vessels' periodicities is not uniform and varies among them, perhaps being one week, ten days, or two weeks, etc. However, this multiple cycle time of the periodicities of vessel arrival patterns, which complicates the yard template decision, is also considered in the model. Moreover, a local branching based solution method and a Particle Swarm Optimization based solution method are developed for solving the model. Numerical experiments are also conducted to validate the effectiveness of the proposed model, which can save around 24% of the transportation costs of yard trucks when compared with the commonly used First-Come-First-Served decision rule. Moreover, the proposed solution methods can not only solve the proposed model within a reasonable time, but also obtain near-optimal results with about 0.1–2% relative gap.     

Sequencing twin automated stacking cranes in a block at automated container terminal

In the considered automated container terminal (ACT) that is designed for Shanghai Yangsha Terminal, two automated stacking cranes (ASCs) are configured for each block and they interact with automated lifting vehicles (ALVs) at the two ends of a block individually. To increase the capacity, container yards with multiple rows of blocks perpendicular to the terminal’s shoreline are considered. To utilize the yard spaces, the twin ASCs are devised to share the same tracks installed at the two sides of a block, while interferences between the ASCs challenge the routing and sequencing operations. To isolate the control and simplify the coordination of the two ASCs, the interference between ASCs is formulated by analyzing the minimal temporal intervals between any two tasks. Three models are then established to sequence the container handling tasks under the minimization of the makespan. An exact algorithm and a genetic algorithm are designed to solve the problem. Numerical experiments show that the algorithms are competitive comparing to on-the-shelf solvers. Practical implications are investigated based on the formulations and experimental results. The managerial implications and technological aspects of applying the formulations and algorithms to practical situations to real-world ACTs are discussed.     

罗天乐大桥水下墩身施工技术

文章根据罗天乐大桥工程地质、水文条件及现场环境特点,结合大桥3#、4#墩工程实例,介绍了水上门吊系统、钢套箱和临时缆索吊装系统的设计及施工方法,为类似工程的水下墩身施工提供参考。     

A frequency-based maritime container assignment model

This paper transfers the classic frequency-based transit assignment method of Spiess and Florian to containers demonstrating its promise as the basis for a global maritime container assignment model. In this model, containers are carried by shipping lines operating strings (or port rotations) with given service frequencies. An origin–destination matrix of full containers is assigned to these strings to minimize sailing time plus container dwell time at the origin port and any intermediate transhipment ports. This necessitated two significant model extensions. The first involves the repositioning of empty containers so that a net outflow of full containers from any port is balanced by a net inflow of empty containers, and vice versa. As with full containers, empty containers are repositioned to minimize the sum of sailing and dwell time, with a facility to discount the dwell time of empty containers in recognition of the absence of inventory. The second involves the inclusion of an upper limit to the maximum number of container moves per unit time at any port. The dual variable for this constraint provides a shadow price, or surcharge, for loading or unloading a container at a congested port. Insight into the interpretation of the dual variables is given by proposition and proof. Model behaviour is illustrated by a simple numerical example. The paper concludes by considering the next steps toward realising a container assignment model that can, amongst other things, support the assessment of supply chain vulnerability to maritime disruptions.     

Improving the performance of rail yards through dynamic reassignments of empty cars

This paper considers the problem of reducing the time that empty cars spend in classification yards of rail systems operating under real-time information and automated schedule-adjustment technologies. The proposed methodology performs dynamic reassignments of empty cars through a fast and efficient solution procedure based on the assignment algorithm. The procedure has been tested on real-life data from one of the major railroads in North America. Computational results show that the procedure runs fast and yields savings in the time that the empty cars spend in the yard.