Joint planning for yard storage space and home berths in container terminals

Yard planning is essential for efficient operations in container terminals, especially for ports with limited storage space. To improve the utilisation of space and the efficiency of container handling in a terminal, operators require flexible yard space planning strategies to manage job workloads and yard-to-berth transportation costs. In previous studies, the inter-related decision making process for berths and yards has normally been studied separately, and yard planning models are designed with deterministic inputs of berths, where many existing terminals are operating with sub-optimal efficiency. In this paper, we consider different policies of the scattered stacking strategy for export containers and analyse the entire cycle of container handling from yard block to home berth, where the home berth is a quay section which includes the preferred berthing place of a vessel upon its arrival. We analyse three stacking policies, namely exclusive, cross-area, and buffer-area stacking policies, and formulate the planning problem for yard storage and related home berths into MILP (mixed integer linear programming) models. Solutions are obtained with a two-stage approach method. The numerical analysis demonstrates that the workload imbalance can be significantly reduced by implementing either the cross-area or buffer-area container stacking policy.     

Yard planning for vessel services with a cyclical calling pattern

In a land-scarce container terminal, congestions in the terminal yard due to highly concentrated workload often lead to unsatisfactory terminal productivity. Currently, yard planners use their experience to design a yard template for determining the storage locations of export containers to be loaded onto vessels deployed to services with a cyclical calling pattern. This article studies the problem of designing a yard template that balances the workload in an export yard. The template design problem is formulated as an integer program. It is found that the computational time required to optimally solve realistic sizes of the template design problem is unacceptably long. This article proposes a simpler integer program as an approximate model. On the basis of the analysis on the approximate model, a heuristic is developed to solve the template design problem. Results of computational experiments show that the heuristic can find effective solutions for the template design problem.     

Flexible space-sharing strategy for storage yard management in a transshipment hub port

In this paper, a storage yard planning problem is studied for a transshipment port with limited space and high-throughput level. Generally, the consignment strategy is used in the yard for a transshipment port, where containers to the same destination vessel are stored together. This is to facilitate faster loading process as it reduces reshuffles as well as long distance movements of yard cranes. However, the consignment strategy is known to be inefficient in space utilization since each storage location must be dedicated to a particular vessel. To improve the space utilization while retaining the advantage of consignment, a new approach named the “flexible space-sharing strategy” is proposed. The idea is that the container space can be shared by two different vessels as long as their containers do not occupy the space at the same time. This strategy allows the same storage location to be reserved for two vessels. The amount of space will only be allocated to a specific vessel on the arrival of corresponding containers. By controlling where to stack the containers in the storage locations, the containers to each vessel are not mixed and the consignment feature can be preserved. This strategy is first formulated as a mixed integer program (MIP). As the MIP model has a block diagonal structure, we develop a search algorithm which combines MIP and heuristics to find the solution. The numerical experiments show that the “flexible space-sharing strategy” can handle much more containers within the same storage space compared with the “non-sharing strategy”.     

Analysis on container port capacity: a Markovian modeling approach

Container ports handle outbound, inbound, and transshipment containers plying between the area for vessels on the quay and the storage space in the yard. Port operators typically concentrate their efforts on the container handling process with the aims of increasing the productivity of quay-side operations and reducing the time in port of vessels. Recognizing that operation processes necessitate containers to stay in the storage space for a certain period before moving to other areas, the operational efficiency at the yard (in addition to that at the quayside) plays an influential role in ensuring performance measures of a container port. This study develops analytical models based on the Markov chain to estimate the port capacity under various combinations of resources, namely, quay cranes, yard cranes, and prime movers. Important performance measures representing the capacity in the proposed models are analyzed and sensitivity analyses of the port capacity are conducted through numerical experiments. The results under the suggested operational strategies are also compared.     

Robust cyclic berth planning of container vessels

We consider a container terminal operator who faces the problem of constructing a cyclic berth plan. Such a plan defines the arrival and departure times of each cyclically calling vessel on a terminal, taking into account the expected number of containers to be handled and the necessary quay and crane capacity to do so. Conventional berth planning methods ignore the fact that, in practice, container terminal operator and shipping line agree upon an arrival window rather than an arrival time: if a vessel arrives within that window then a certain vessel productivity and hence departure time is guaranteed. The contributions of this paper are twofold. We not only minimize the peak loading of quay cranes in a port, but also explicitly take into account the arrival window agreements between the terminal operator and shipping lines. We present a robust optimization model for cyclic berth planning. Computational results on a real-world scenario for a container terminal in Antwerp show that the robust planning model can reach a substantial reduction in the crane capacity that is necessary to meet the window arrival agreements, as compared to a deterministic planning approach.     

An effective heuristic for scheduling a yard crane to handle jobs with different ready times

In land-constrained port container terminals, yard cranes are commonly used for handling containers in a container yard to load containers onto or unload containers from trucks. However, yard cranes are bulky, slow and need to move frequently between their work locations. As it is common that the container flow in a terminal is bottlenecked by yard crane operations, effective work schedules of yard cranes are needed to increase the terminal’s throughput. This article studies the problem of scheduling a yard crane to perform a given set of container handling jobs with different ready times. The objective is to minimize the sum of job waiting times. It is noted that the scheduling problem is NP-complete. This research develops a heuristic to solve the scheduling problem and an algorithm to find lower bounds for benchmarking the schedules found by the heuristic. The performance of the heuristic is evaluated by a set of test problems generated on the basis of real-life terminal operations data. Indeed, the computational results show that the proposed heuristic can find effective solutions for the scheduling problem.     

A yard storage strategy for minimizing traffic congestion in a marine container transshipment hub

This paper studies a storage yard management problem in a transshipment hub where the loading and unloading activities are both heavy and concentrated. In order to reduce the number of reshuffles, which helps to reduce the vessel turnaround time, the port operator uses the consignment strategy to group export and transshipment containers according to their destination vessel. To reduce the potential traffic congestion of prime movers, a high–low workload balancing protocol is used. A mixed integer programming model is formulated to determine the storage locations of incoming containers, the number of incoming containers and the smallest number of yard cranes to deploy in each shift. An iterative improvement method is developed to solve the problem, in which a tabu search based heuristic algorithm is used to generate an initial yard template, and then the generated yard template is improved by an improvement algorithm iteratively until an optimal or a satisfactory solution is obtained. Experiment results show that the proposed method can generate excellent results within a reasonable time, even for the extreme cases.     

Development and simulation analysis of real-time yard crane control systems for seaport container transshipment terminals

As more and more container terminals open up all over the world, terminal operators are discovering that they must increase quay crane work rates to remain competitive. In this paper, we develop a real-time yard crane control system and show that a terminal’s long-run average quay crane rate depends on the portion of this system that dispatches yard cranes in the storage area in real time. Several real-time yard crane dispatching systems are evaluated by a fully-integrated, discrete event simulation model of a pure transshipment terminal that is designed to reproduce the multi-objective, stochastic, real-time environment at an RTGC-based, multiple-berth facility. Results indicate that yard cranes should prioritize the retrieval of containers from the stacks, rather than the storage of containers into stacks. Also, the yard crane dispatching system should not only consider the trucks already waiting for service in the yard, but also the trucks that are heading towards the yard. The experiments provide the first direct connection in the literature between real-time yard crane control systems and long-run performance at a seaport container terminal. We also make a qualitative comparison between rule-based and look-ahead yard crane dispatching schemes, and discuss deadlocking issues in detail.     

A sample average approximation approach to the berth allocation problem with uncertain tides

The remarkable increases in containerized trade over the past few years have resulted in increased congestion and operational costs of container terminals, indicating the importance of the effective management of port resources under uncertainty. In this article, a novel berth allocation model is suggested for seaports, taking into consideration the disruptive effects of tides on the berthing schedule as well as the uncertainty in the arrival time of vessels. A rigorous mathematical model is presented along with a sample average approximation method to generate an efficient berth allocation plan. In addition, statistical analysis of real data gathered from a real case is presented. Numerical analysis has been conducted to verify the practical applications of the model proposed for the berth allocation problem under uncertainty. Computational results based on a real-world data set provided by Rajaee port, Iran, demonstrate the effectiveness of the proposed solution method.     

Performance analysis of berth configurations at container terminals

The containerized trade market has been growing rapidly since its introduction. The capacity of ships and the amount of containers being transshipped at container terminals increases significantly. Terminals should handle their operations efficiently to provide the necessary capacity and customer service. In designing a container terminal, terminal management has to consider the choice for a certain type of berth. In this paper, we compare by means of a simulation study the performance of traditional one-sided marginal berths and indented berths. An indented berth enables quay cranes to unload and load containers from both sides of the ship. As a result, more quay cranes can work on a single ship. As main performance measure in this comparison we use the total vessel operation time required to unload and load a ship. This time depends next to crane productivity also on the efficiency of the transportation and storage and retrieval processes in the terminal. We have performed a sensitivity analysis in which we also study the relation between the selection of an indented berth and other design and control issues in the terminal.     

求解集装箱堆场堆垛问题的约束满足算法

集装箱堆垛问题普遍存在于港口码头堆场作业管理中,是在集装箱数目已知的前提下,要求满足交货期限制、重量限制以及垛位高度限制等约束条件,目标是实现占用垛位数最少。通过问题分析,将其归结为一类带顺序约束的装箱问题,并建立了约束满足优化模型,设计了嵌入经典装箱启发式原则的约束满足求解算法。为了验证模型和算法的可行性和有效性,根据某集装箱码头堆场的实际生产情况构造测试算例,实验结果表明,该算法对于实现垛位数最小化、求解复杂约束下的大规模堆场问题较现有的装箱启发式有一定程度的改善。     

Dispatching vehicles in a mega container terminal

We consider a container terminal discharging and uploading containers to and from ships. The discharged containers are stored at prespecified storage locations in the terminal yard. Containers are moved between the ship area and the yard using a fleet of vehicles, each of which can carry one container at a time. The problem is to dispatch vehicles to the containers so as to minimize the total time it takes to serve a ship, which is the total time it takes to discharge all containers from the ship and upload new containers onto the ship. We develop easily implementable heuristic algorithms and identify both the absolute and asymptotic worst-case performance ratios of these heuristics. In simple settings, most of these algorithms are optimal, while in more general settings, we show, through numerical experiments, that these algorithms obtain near-optimal results for the dispatching problem.Research was supported in part by the Port of Singapore Authority (PSA).     

How to park freight trains on rail–rail transshipment yards: the train location problem

In modern rail–rail transshipment yards huge gantry cranes spanning all railway tracks allow for an efficient transshipment of containers between different freight trains. This way, multiple trains loaded with cargo for varying destinations can be consolidated to a reduced number of homogeneous trains, which is an essential requirement of hub-and-spoke railway systems. An important problem during the daily operations of such a transshipment yard is the train location problem, which assigns each train of a given pulse to a railway track (vertical position) and decides on each train’s parking position on the track (horizontal position), so that the distances of container movements are minimized and the overall workload is equally shared among cranes. For this problem a mathematical model is presented; different heuristic solution procedures are described and tested in a comprehensive computational study. The results show that our procedures allow for a remarkable reduction of train processing time compared with typical real-world train location policies.     

Optimizing the yard layout in container terminals

The main activities of container terminals are to load outbound containers on to vessels, discharge inbound containers from vessels, and store those containers in the yard before loading (or after discharging) them. This study proposes a method for determining an optimal layout of container yards taking into consideration the storage space requirements and throughput capacities of yard cranes and transporters. Two types of yard layout are under consideration: a layout where blocks are laid out parallel to the quay and transfer points are located beside a bay per block, and a layout whose blocks are laid out perpendicular to the quay and transfer points are located at both ends of each block. Various cost factors are used for optimizing the yard layout, which include the construction cost of the ground space, the fixed overhead cost of yard cranes, and the operating costs of yard cranes and transporters. Sensitivity analysis is performed to investigate the effect of various design parameters on the optimal layout of the yard. The two types of yard layout are compared with each other, and the results of this study are compared against those for real-world yard layouts from the perspective of throughput capacity and storage space capacity.     

An optimization model for storage yard management in transshipment hubs

This paper studies a yard storage allocation problem in a transshipment hub where there is a great number of loading and unloading activities. The primary challenge is to efficiently shift containers between the vessels and the storage area so that reshuffling and traffic congestion is minimized. In particular, to reduce reshuffling, a consignment strategy is used. This strategy groups unloaded containers according to their destination vessel. To reduce traffic congestion, a new workload balancing protocol is proposed. A mixed integer-programming model is then formulated to determine the minimum number of yard cranes to deploy and the location where unloaded containers should be stored. The model is solved using CPLEX. Due to the size and complexity of this model two heuristics are also developed. The first is a sequential method while the second is a column generation method. A bound is developed that allows the quality of the solution to be judged. Lastly, a numerical investigation is provided and demonstrates that the algorithms perform adequately on most cases considered.     

Storage allocation in transshipment hubs under uncertainties

The state-of-the-art methods for yard storage allocation seldom consider uncertain factors, e.g. unexpected changes of loading/unloading time of vessels, workloads in each time shift, etc. All of these unforeseen events may reduce the efficiency of the initial plan and even render it infeasible. This paper firstly investigates the recovery strategy in yard storage allocation, which is the traditional way for handling uncertainties, whereas it could not be effective for universal situations and may fail in some complex circumstances. Thus, this paper proposes a real-time decision support system (DSS) which can act as an ultimate solution for coping with uncertainties in yard storage allocation process. This DSS is oriented to the planning for one time shift under the dynamic yard template, hence enables port operators to cope with flexible volume of arriving containers and uncertainties in the realistic circumstances. Some numerical experiments are performed to validate that the proposed real-time DSS has better performances than traditional methods in flexible and dynamic environments.     

Synchronization of yard truck scheduling and storage allocation in container terminals

Yard truck scheduling and storage allocation, as two separate subproblems in port operations, have been extensively studied in the past decades. However, from the operational point of view, they are highly interdependent. This article proposes an integer programming model in which yard truck scheduling and storage allocation problems are formulated as a whole for heterogeneous import containers. Different stacking times at yard blocks is modelled as well. The objective of the proposed model is to reduce the congestion and waiting time of yard trucks in the terminal so as to decrease the makespan of discharging containers. Owing to the inherent computational complexity, a genetic algorithm and a greedy heuristic algorithm have been designed. Computational experiments show that the proposed genetic algorithm and greedy algorithm are both effective in solving the studied problem.     

Data envelopment analysis of AGV fleet sizing at a port container terminal

A decision-making approach based on Data Envelopment Analysis (DEA) for determining the efficient container handling processes (considering the number of employed Automated Guided Vehicles (AGVs)) at a port container terminal (PCT) is presented in this paper. Containers are unloaded from the ship by quay cranes and transported to the storage area by AGVs. We defined performance measures of proposed container handling processes and analysed the effects when changing the number of AGVs. The values of performance measures were collected and/or calculated from simulation. Container handling process, with a fixed number of quay cranes, when a different number of AGVs is used to transport containers from berth to assigned locations within storage area, represents a decision-making unit (DMU). We applied the basic CCR (Charnes, Cooper and Rhodes) DEA model with two inputs: average ship operating delay costs and average operating costs of employed equipment at a PCT, and two outputs: average number of handled import containers per ship and weighted average utilisation rate of equipment at a PCT. DEA method proved to be useful when testing different DMUs and when determining efficient DMUs for planning purposes. This study shows that efficiency evaluation of AGV fleet sizing and operations is useful for planning purposes at PCTs.     

Positioning of loading units in a transshipment yard storage area

This paper considers a decision problem as it arises in a rail–road transshipment yard when unloading a bundle of trains. The loading units, e.g. containers, arriving on trains and occasionally arriving on trucks have to be placed on storage lanes of limited capacity. Loading units are placed and removed keeping stacking and crane rail moves small. We present two NP-hard models and some heuristics for solving the problem. One of these heuristics is currently applied at the yard. The algorithms are then tested using real-life data.     

Development and simulation analysis of real-time, dual-load yard truck control systems for seaport container transshipment terminals

We show how a seaport container terminal’s long-run average quay crane rate depends on the system that automatically assigns yard trucks to container transportation jobs in the terminal in real time. Several real-time, dual-load yard truck control systems are proposed and evaluated by a fully-integrated, discrete event simulation model of a vessel-to-vessel transshipment terminal. The model is designed to reproduce the microscopic, stochastic, real-time environment at a multiple-berth facility. Overall, the literature still lacks a comprehensive analysis that (1) considers different methods for controlling dual-load vehicles in real time within a fully-integrated, stochastic container terminal environment and (2) compares them in terms of an absolute global performance measure such as average quay crane rate. This paper provides such an analysis.