Heuristic-based truck scheduling for inland container transportation

A truck scheduling problem for container transportation in a local area with multiple depots and multiple terminals including containers as a resource for transportation is addressed. Four types of movements of containers as inbound full, outbound full, inbound empty and outbound empty movements as well as the time windows at both the origin and the destination are considered. The total operating time of all trucks in operation is taken as the optimization criterion that has to be minimized. The problem is mathematically modeled based on a preparative graph formulation and falls into an extension of the multiple traveling salesman problem with time windows (m-TSPTW). The window partition based solution method for the m-TSPTW in Wang and Regan (Transp Res Part B: Methodol 36:97–112, 2002) is modified so that its computation time is reduced greatly. The experiments based on a number of randomly generated instances indicate that the modified method is quite fast and the quality of solutions is relatively high for the m-TSPTW. These experiments also demonstrate that our approach is able to generate high-quality results for the equivalent truck scheduling and inland container movement problem in container drayage operations.     

Effects of storage block layout and automated yard crane systems on the performance of seaport container terminals

As a decoupling point between waterside and landside transport, the container yard plays a major role for the competitiveness of container terminals. One of the latest trends in container yard operations is the automated rail-mounted-gantry-crane system, which offers dense stacking along with high productivity. In this paper, the strategic design of rail-mounted-gantry-crane systems is investigated. A simulation study is conducted to evaluate the effects of four rail-mounted-gantry-crane systems and 385 yard block layouts—differing in block length, width, and height—on the yard and terminal performance.     

Disruption recovery model for berth and quay crane scheduling in container terminals

This article addresses the problem of recovering berth and quay crane (QC) schedules in container terminals when disruptions occur after a subset of operations has been processed. Firstly, models for simultaneous optimization of berth and QC schedules are developed. Then, two strategies, namely, QC rescheduling strategy and berth reallocation strategy are proposed to tackle disruptions and recover the berth and QC schedule, and models for the two strategies are developed respectively. To solve the disruption recovery models, algorithms based on local rescheduling and tabu search are designed. Finally, numerical experiments are provided to illustrate the validity of the proposed model and algorithms.     

自动化集装箱码头运输系统配置的仿真优化

以新型自动化集装箱码头中间运输系统为研究对象,建立了自动化集装箱码头中间运输系统的仿真优化模型,并利用仿真优化方法搜索优化调度方案,最小化船舶靠岸后装卸作业的总时间和最大化各种设备的操作效率,优化模块使用遗传算法,整个程序使用C#语言编制.通过仿真计算表明能够非枚举地从所有可能的动态调度方案中搜到最佳方案:运输系统的设备利用率、系统作业时间,都得到了相应改善.     

A scheduling method for Berth and Quay cranes

This paper discusses a method for scheduling Berth and Quay cranes, which are critical resources in port container terminals. An integer programming model is formulated by considering various practical constraints. A two-phase solution procedure is suggested for solving the mathematical model. The first phase determines the Berthing position and time of each vessel as well as the number of cranes assigned to each vessel at each time segment. The subgradient optimization technique is applied to obtain a near-optimal solution of the first phase. In the second phase, a detailed schedule for each Quay crane is constructed based on the solution found from the first phase. The dynamic programming technique is applied to solve the problem of the second phase. A numerical experiment was conducted to test the performance of the suggested algorithms. RID="*" ID="*" This research has been supported in part by Brain Korea 21 Program (1999–2002). Correspondence to: Y.-M. Park     

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.     

Operations research at container terminals: a literature update

The current decade sees a considerable growth in worldwide container transportation and with it an indispensable need for optimization. Also the interest in and availability of academic literatures as well as case reports are almost exploding. With this paper an earlier survey which proved to be of utmost importance for the community is updated and extended to provide the current state of the art in container terminal operations and operations research.     

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.     

Comparison of vehicle types at an automated container terminal

At automated container terminals, containers are transshipped from one mode of transportation to another. Automated vehicles transport containers from the stack to the ship and vice versa. Two different types of automated vehicles are studied in this paper, namely automated lifting vehicles and automated guided vehicles. An automated lifting vehicle is capable of lifting a container from the ground by itself. An automated guided vehicles needs a crane to receive and deliver a container.In designing automated container terminals one have to consider the choice for a certain type of equipment. The choice for a certain type of equipment should be made by performing a feasibility and economic analysis on various types of equipment. In this paper, we examine effects of using automated guided vehicles and automated lifting vehicles on unloading times of a ship, with simulation studies. In choosing a certain type of equipment we have considered criteria such as unloading times of a ship, occupancy degrees and the number of vehicles required. 38% more AGVs need to be used than ALVs. From this specific study, we conclude that, by observing only purchasing costs of equipment, ALVs are a cheaper option than AGVs.To obtain an accurate analysis we have performed a sensitivity analysis. It can be concluded that the design of the terminal and technical aspects of quay cranes impact the number of vehicles required and as a result the choice for a certain type of equipment. Correspondence to: Iris F. A. Vis     

Scheduling operations of a rail crane and container deliveries between rail and port terminals

This article addresses the problem of scheduling container transfer operations in rail terminals. The overall problem can be divided into three smaller problems: constructing a dual-cycle delivery task by matching inbound and outbound containers; determining parking positions for trucks; and sequencing the delivery tasks for transfer by the rail crane. This article provides a mathematical model to obtain the optimal solutions to these problems, and suggests genetic and heuristic algorithms to reduce computational time when solving larger problems. Numerical experiments are conducted to validate the performance of the suggested heuristic algorithms.