Yard Crane Research Articles

Joint Deployment of Quay Cranes and Yard Cranes in Container Terminals at a Tactical Level

This paper discusses tactical joint quay crane (QC) and yard crane (YC) deployment in container terminals. The deployments of QCs and YCs are critical for the efficiency of container terminals. Although they are closely intertwined, the deployments of QCs and YCs are usually sequential. This paper proposes a mixed-integer programming model for the joint deployment of QCs and YCs in container terminals. The objective of the model is to minimize the weighted vessel turnaround time and the weighted delayed workload for external truck service in yard blocks, both of great importance for a container terminal but rarely considered together in the literature. This paper proves that the studied problem is NP-hard in the strong sense. Case studies demonstrate that the proposed model can obtain better solutions than the sequential method. This paper also investigates the most effective combinations of QCs and YCs for a container terminal at various demand levels.

Two Yard Crane Scheduling With Dynamic Processing Time and Interference

Maritime transportation is an important branch of intelligent transportation system (ITS). It is widely recognized that modern ITS technologies and advanced management methods, such as automated yard crane (YC) planning and scheduling, can significantly improve container terminal performance, and also impact the global performance of maritime transportation. In this paper, we investigate two YC scheduling with storage and retrieval tasks in a container block. The main contributions of this paper are: 1) container reshuffling operations and inter-crane interference constraint are both considered and 2) the dynamic processing times for retrieval containers are taken into consideration. These typical YC operation characteristics complicate the YC scheduling, and cause late delivery and economic loss. In this study, we focus on minimizing the maximum tardiness of container task and establishing an integer linear programming model. Regarding the NP-hardness nature of the problem, we develop a heuristic named dividing, sequencing, and comparing (DSC) and a genetic algorithm (GA) based on the characteristics of the problem. The computational results show the efficient performance of the developed algorithms, compared with the exact solutions via Cplex software for small size instances. The efficiency and effectiveness of DSC outperform those of GA for practical size instances.

Yard crane scheduling to minimize total weighted vessel loading time in container terminals

One of the most important objectives for container terminals is to minimize the total weighted turnaround time for vessels. Minimizing total weighted vessel loading time directly helps minimize total weighted vessel turnaround time. In this paper we consider the yard crane (YC) scheduling problem in a multi-vessel loading process. We propose a YC scheduling system that minimizes the total weighted maximum tardiness of loading jobs. Our experiments show that this is significantly more effective in the minimization of the total weighted vessel loading time than the existing YC scheduling methods that minimize job waiting time or makespan. Our scheduling system also has the ability to dynamically optimize the YC operations with the consideration of the maximum tardiness already incurred to each vessel earlier in the loading process. To evaluate against our YC scheduling system, an optimal algorithm to minimize makespan (useful if there is YCs shortage) and an optimal algorithm to minimize total weighted job tardiness (common in manufacturing) are also proposed.

Integrated scheduling of handling operations in railway container terminals

The railway handling area of the railway container terminal is the main place for container sea–rail transportation. To enhance the efficiency of the handling systems and improve the coordination of different types of equipment in railway handling area, an integrated scheduling model is developed, which integrates the scheduling of rail-mounted gantry cranes (GCs), inner trucks (ITs), and yard cranes (YCs). This model considers not only train loading and unloading simultaneously, but GC interference and safety margin, GC and YC travel time as well as buffer area. A multi-layer genetic algorithm (MLGA) is proposed to solve the problem. Eventually, comparison experiments are conducted, including the experiments on handling process between non-optimization and optimization, MLGA with and without the balanced operator and the performance of different numbers of ITs. These experiments validate that the model and algorithm is feasible and efficient in both equipment scheduling and allocation problem.

A branch-and-price method for integrated yard crane deployment and container allocation in transshipment yards

With the trend towards mega-vessels and shipping alliance, the importance of transshipment activities keeps increasing. In transshipment yards, a “yard template” is often used to stack containers in dedicated areas (sub-blocks) pre-reserved for their own destination vessels. At short-term planning level, the yard template is given, but the containers going to a specific vessel still have high flexibility to be allocated among many pre-reserved sub-blocks. The amount of containers allocated to each sub-block, i.e. “container allocation”, not only affects the traffic congestion, but more importantly determines the number of yard cranes (YCs) required in each block. The limited YCs have to switch blocks to fit the needs of container allocation in different periods, i.e. “YC deployment”. This study integrated these two closely related problems and formulated a MIP model. Since the model has a nice block-diagonal structure, column generation under Dentzig Wolfe decomposition was proposed to get lower bounds. A novel branch-and-price (B&P) method was proposed to find near-optimal solutions. To reduce the searching tree size, our B&P method branched on YC paths during the planning horizon, instead of branching on decision variables directly. Numerical experiments under both small and large scale problems showed that our B&P method could efficiently solve the integrated planning problem. The results also showed that YC movements could be reduced effectively without sacrificing operational efficiency or using more yard cranes.

Scheduling for yard cranes based on two-stage hybrid dynamic programming

Making operational plans for Yard Cranes (YCs) to enhance port efficiency has become vital issues for the container terminals. This paper discusses the load-scheduling problem of multiple YCs. The problem is to schedule two YCs at different container blocks, which serve the loading operations of one quay crane so as to minimize the total distance of visiting paths and the make-span at stack area. We consider the container handling time, the YC visiting time, and the waiting time of each YC when evaluating the make-span of the loading operation by YCs. Both the container bay visiting sequences and the number of containers picked up at each visit of the two YCs are determined simultaneously. A mathematical model, which considers interference between adjacent YCs, is provided by means of time-space network to formulate the problem and a two-stage hybrid algorithm composed of greedy algorithm and dynamic programming is developed to solve the proposed model. Numerical experiments were conducted to compare performances of the algorithm in this study with actual scheduling rules.

A network model for solving the yard truck routing and scheduling problem

Purpose – The purpose of this paper is to improve the efficiency of loading and discharging operations in container terminals. Accounting for an increase in the size of ships, the yard truck (YT) routing and scheduling problem has become an important issue to terminal operators. Design/methodology/approach – A (binary) integer programming model is developed using the time-space network technique to optimally move YTs between quay cranes (QC) and yard cranes (YC) in the time and space dimensions. The objective of the model is to minimize the total operating cost, and the model employs the M/M/S model in the queuing theory to determine the waiting time of YTs. The developed model can obtain the optimal number of YTs and their scheduling and routing plans simultaneously, as shown by the computational results. Findings – The results also show that the model can be applied to practical operations. In this research, an experimental design of the QC and YC operation networks was considered with the import and export containers carried by YTs. The model can be used to tackle a real world problem in an international port, and the analysis results could be useful references for port operators in actual practice. Research limitations/implications – The purpose of this research only focusses on YTs routing and scheduling problem, however, the container terminal operation problems are interrelated with berth allocation and yard stacking plan. The managerial application of this study is to analyze the trade-off between truck numbers and truck waiting time can be used for terminal operators to adjust the truck assignment. This research can assist an operator to determine the optimal fleet size and schedule in advance to avoid wasted costs and congestion in the quayside and yard block. Originality/value – This research solves the YT scheduling and routing problem for container discharging and loading processes with a time-space network model, which has not been previously reported, through an empirical research.

A Proactive Approach for Yard Crane Scheduling Problem with Stochastic Arrival and Handling Time

For a container terminal system, efficient yard crane (YC) schedules have great impact on the improvement of both operation efficiency and customer satisfaction. In this paper we address yard crane problem with uncertainties of vessels or trucks arrival time and container handling time. Vessels and trucks arrive dynamically with different service priorities and total number of handling containers is allowed to be changeable on current recording, adding more flexibility to the terminal system. A mixed integer programming model is proposed, and a simulation based Genetic Algorithm (GA) search procedure is applied to generate robust YC schedule proactively. Computational experiments are conducted to show the satisfied performance of our development method under uncertainty.

Integrated internal truck, yard crane and quay crane scheduling in a container terminal considering energy consumption

Container terminals mainly include three types of handling equipment, i.e., quay cranes (QCs), internal trucks (ITs) and yard cranes (YCs). Due to high cost of the handling equipment, container terminals can hardly purchase additional handling equipment. Therefore, the reasonable scheduling of these handling equipment, especially coordinated scheduling of the three types of handling equipment, plays an important role in the service level and energy-saving of container terminal. This paper addresses the problem of integrated QC scheduling, IT scheduling and YC scheduling. Firstly, this problem is formulated as a mixed integer programming model (MIP), where the objective is to minimize the total departure delay of all vessels and the total transportation energy consumption of all tasks. Furthermore, an integrated simulation-based optimization method is developed for solving the problem, where the simulation is designed for evaluation and optimization algorithm is designed for searching solution space. The optimization algorithm integrates genetic algorithm (GA) and particle swarm optimization (PSO) algorithm, where the GA is used for global search and the PSO is used for local search. Finally, numerical experiments are conducted to verify the effectiveness of the proposed method. The results show that the proposed method can coordinate the scheduling of the three types of handling equipment and can realize the optimal trade-off between time-saving and energy-saving.

Yard crane scheduling in a container terminal for the trade-off between efficiency and energy consumption

Green transportation has recently been the focus of the transportation industry to sustain the development of global economy. Container terminals are key nodes in the global transportation network and energy-saving is a main goal for them. Yard crane (YC), as one type of handling equipment, plays an important role in the service efficiency and energy-saving of container terminals. However, traditional methods of YC scheduling solely aim to improve the efficiency of container terminals and do not refer to energy-saving. Therefore, it is imperative to seek an appropriate approach for YC scheduling that considers the trade-off between efficiency and energy consumption. In this paper, the YC scheduling problem is firstly converted into a vehicle routing problem with soft time windows (VRPSTW). This problem is formulated as a mixed integer programming (MIP) model, whose two objectives minimize the total completion delay of all task groups and the total energy consumption of all YCs. Subsequently, an integrated simulation optimization method is developed for solving the problem, where the simulation is designed for evaluating solutions and the optimization algorithm is designed for exploring the solution space. The optimization algorithm integrates the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm, where the GA is used for global search and the PSO is used for local search. Finally, computational experiments are conducted to validate the performance of the proposed method.

An efficient approach for solving yard crane scheduling in a container terminal

An efficient approach for yard crane (YC) scheduling is proposed in this paper. The definition of task group for YC scheduling is proposed. A mixed integer programming (MIP) model is developed. In the model, objective functions are subject to the minimization of the total delay of complete time for all task groups and the minimization of block-to-block movements of YCs. Due to the computational scale of the non-deterministic polynomial (NP) complete problem regarding YC scheduling, a rolling-horizon decision-making strategy is employed to solve this problem, by converting the MIP model into another MIP model in the scheduling of each rolling period. Afterwards, a heuristic algorithm based on modified A* search is developed to solve the converted model and obtain near optimal solution. Finally, the computational experiments are used to examine the performance of the proposed approach for YC scheduling.

Dynamic Space and Time Partitioning for Yard Crane Workload Management in Container Terminals

We propose a new hierarchical scheme for yard crane (YC) workload management in container terminals. We also propose a time partitioning algorithm and a space partitioning algorithm for deploying YCs to handle changing job arrival patterns in a row of yard blocks. The main differences between our approach and most of the methods in literature are (1) the average vehicle job waiting time instead of the number of jobs is used to balance YC workload and to evaluate the quality of a partition, (2) the YC working zone assignment is not in units of yard blocks and our space partitioning algorithm generates more flexible divisions of the workload from all blocks, and (3) the YC deployment frequency is not fixed but is decided by our time partitioning algorithm with the objective of minimizing average vehicle waiting times. The scheme combines simulation and optimization to achieve our objective for a row of yard blocks. Experimental results show that the proposed binary partitioning algorithm TP2 makes substantial improvements in job waiting times over the basic partitioning scheme and another existing algorithm (Ng, W. C. 2005. Crane scheduling in container yards with intercrane interference. Eur. J. Oper. Res. 164(1) 64–78) in all tested job arrival scenarios.

A continuous time model for multiple yard crane scheduling with last minute job arrivals

Container terminal (CT) operations are often bottlenecked by slow yard crane (YC) movements. Efficient YC scheduling to reduce the PM waiting time is therefore critical in increasing a CT’s throughput. This chapter develops an efficient continuous-time MILP model for YC scheduling. The model treats realistic operational constraints such as multiple intercrane interference, fixed YC separation distances, simultaneous container storage/retrievals, realistic YC acceleration/deceleration stages and gantry time, and require far fewer integer variables than previous work. The model significantly improves the solution quality compared to the existing discrete-time models and other heuristics found in the literature. Using heuristics and a rolling-horizon algorithm, our model can solve actual container yard (CY) problems quickly and robustly in polynomial time. Also, to cope with the last-minute container arrivals which can disrupt routine CT operations, two methods for handling these last-minute job insertions are discussed and compared.

Discrete time model and algorithms for container yard crane scheduling

Container terminal (CT) operations are often bottlenecked by slow YC (yard crane) movements. PM (prime mover) queues in front of the YCs are common. Hence, efficient YC scheduling to reduce the PM waiting time is critical in increasing a CT's throughput. We develop an efficient model for YC scheduling by taking into account realistic operational constraints such as inter-crane interference, fixed YC separation distances and simultaneous container storage/retrievals. Among them, only inter-crane interference has ever been considered in the literature. The model requires far fewer integer variables than the literature by using bi-index decision variables. We show how the model can be solved quickly using heuristics and rolling-horizon algorithm, yielding close to optimal solutions in seconds. The solution quality and solution time are both better than the literature even with additional constraints considered. The proposed formulations and algorithms can be extended to other problems with time windows and space constraints.

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.

Simultaneous Load Scheduling of Quay Crane and Yard Crane in Port Container Terminals

Load scheduling problems of the quay crane (QC) and yard crane (YC) are important issues in port container terminal operations. Because the two scheduling problems are closely related, this paper proposes a mathematical model to formulate the load scheduling problem of the QC and YC simultaneously. A genetic algorithm (GA) and a heuristic method [QC and YC scheduling heuristic (QYSH)] are designed for the problem solution. Results obtained through numerical experiments showed that the problem-oriented QYSH method significantly outperformed the GA and could be applied in real operations to conduct simultaneous quay crane and yard crane scheduling.

POSCO YARD CRANE AUTOMATION

This paper describes an integrated approach for crane automation at the Kwangyang steel works, POSCO. Unmanned cranes are composed of several technologies, which include anti-sway control, precision position control, optimal trajectory computation, and coil shape recognition. Crane position while traveling and the traverse axis are controlled by PID position controllers. In order to prevent swaying during crane operation, the sway angle is consistently suppressed from the start point to the destination using an anti-sway algorithm. For optimal trajectory control, 3-axis motion was analyzed and variable speed drives were used. A 3D object recognition system for picking up coils, based on stereo vision, is in progress. Some of the described control strategies have been successfully applied to the 10-1 crane in the No. 4 CGL (Continuous Galvanizing Line) of the Kwangyang steel works, POSCO. Substantial cost reduction and improved productivity are expected benefits of crane yard automation.

99/00708 Reduction of blast furnace coke rate: coal injection

This paper describes an integrated approach for crane automation at the Kwangyang steel works, POSCO. Unmanned cranes are composed of several technologies, which include anti-sway control, precision position control, optimal trajectory computation, and coil shape recognition. Crane position while traveling and the traverse axis are controlled by PID position controllers. In order to prevent swaying during crane operation, the sway angle is consistently suppressed from the start point to the destination using an anti-sway algorithm. For optimal trajectory control, 3-axis motion was analyzed and variable speed drives were used. A 3D object recognition system for picking up coils, based on stereo vision, is in progress. Some of the described control strategies have been successfully applied to the 10-1 crane in the No. 4 CGL (Continuous Galvanizing Line) of the Kwangyang steel works, POSCO. Substantial cost reduction and improved productivity are expected benefits of crane yard automation.

On Multilevel Optimization of a Combined Static and Dynamic Problem

The solution of a combined static and dynamic optimization problem is considered in this paper. By means of a feasible decomposition procedure this combined problem is first decomposed into a two-level optimization problem. In this new problem the first-level subproblem is found to be one of conventional optimal control and mathematical programming which can be solved using known techniques. For the solution of the second-level problem a computational algorithm is developed using the gradient projection method. The existence of the solution is investigated. To illustrate the applicability of the method, a simplified gantry crane yard design problem is considered and some computational results are given.