Crane Deployment Research Articles

Effect of block length and yard crane deployment systems on overall performance at a seaport container transshipment terminal

As more and more container terminals open up all over the world, terminal operators are discovering that they must increase quay crane work rates in order to remain competitive. In this paper we present a simulation study that shows how a terminal's long-run average quay crane rate depends on (1) the length of the storage blocks in the terminal's container yard and (2) the system that deploys yard cranes among blocks in the same zone. Several different block lengths and yard crane deployment systems are evaluated by a fully dynamic, discrete event simulation model that considers the detailed movement of individual containers passing through a vessel-to-vessel transshipment terminal over a several week period. Experiments consider four container terminal scenarios that are designed to reproduce the multi-objective, stochastic, real-time environment at a multiple-berth facility. Results indicate that a block length between 56 and 72 (20-ft) slots yields the highest quay crane work rate, and that a yard crane deployment system that restricts crane movement yields a higher quay crane work rate than a system that allows greater yard crane mobility. Interestingly, a block length of 56–72 slots is somewhat longer than the average block in use today. The experiments provide the first direct connection in the literature between block length and long-run performance at a seaport container terminal. The simulator can be suitably customized to real, pure-transshipment ports and adequately tuned to get an appreciable prescriptive power.

Container Assignment and Yard Crane Deployment in a Container Terminal: A Case Study

Vessels and seaports are an essential part of world trade and economy. Owing to soaring competition between the container terminals and pressure from shipping lines to shorten the vessel port stay, operations research techniques are continuously being developed to enhance terminal performance and efficiency. However, many of these studies only focus on a single area of the terminal operations, such as vehicle routing or berth planning. Although optimising the performance of each individual operation is fundamental to overall terminal efficiency, the interrelations between the various decisions should also be examined in detail as a decision taken in one area at an early stage may have a significant impact on downstream operations. The purpose of this paper is to develop a unified approach within which the container assignment and yard crane deployment problems arising within a given planning time horizon are considered simultaneously. We have developed a new mathematical formulation of the combined problem with the view to finding optimal container flows through the yard that minimise the overall storage and handling cost. The paper presents a description of the proposed modelling approach and a practical application for the Port of Felixstowe. Preliminary computational results are reported.

An investigation into dynamic yard crane deployment and comparisons between hill-climbing and best-first-search algorithms

Container terminals secure a crucial position in container transportation, including shipping and land transportation. In particular, container yard management, which involves diverse operational services, significantly affects the operational efficiency of the entire container terminal. However, it is imperative to attain an effective workload scheduling to support the dynamic deployment of yard cranes. Based on these understandings, the proposed system aims at postulating a novel strategy in terms of yard crane scheduling. In this manner, a dynamic allocation model is initially developed using integer programming for yard cranes. To resolve the NP-hard problem regarding the yard crane deployment, two heuristic algorithms, i.e., the hill-climbing algorithm and the best-first-search algorithm, are then employed. A case study on a specific container terminal yard is used for system illustration via a simulation approach. Consequently, comparisons are conducted based on the results obtained from the hill-climbing and best-first-search algorithms.

Finding the Number of Yard Cranes Needed to Achieve Desired Truck Turn Time at Marine Container Terminals

Because of environmental concerns, terminals are increasingly looking to reduce their truck turn time. Terminals are also looking to reduce truck turn time so that they can lower the inland transportation cost of shipping a container. For terminals that stack their containers, the solution may seem obvious: add more yard cranes. However, the high cost of those cranes often prohibits terminals from freely buying more. Another reason terminals are reluctant to add more yard cranes is that there is no clear understanding of how yard cranes affect truck turn time. A study introduces a simulation model for the analysis of truck turn time with respect to crane availability and deployment. This effort is accomplished by modeling the precise movements of trucks and yard cranes. The developed model uses the Barbours Cut Container Terminal of the Port of Houston Authority as a test bed to demonstrate how it can be applied to find the number of yard cranes needed to achieve a desired truck turn time. Other uses of the model include testing the crane deployment methodology, examining the effect of crane failure, and analyzing the impact of an appointment system.

Rubber tired gantry crane deployment for container yard operation

Container terminal's competitiveness is generally measured by the vessel discharging and loading time. The shore crane operation has attracted a number of research works. However, yard operation management has been very much experience based and did not receive much attention until last decade. This paper presents an algorithm and a mathematical model for the optimal yard crane deployment. The potential of the model in optimizing yard crane deployment was tested with a set of real operation data extracted from a major container yard terminal.

A heuristic for dynamic yard crane deployment in a container terminal

Rubber Tired Gantry Cranes (RTGCs) are the most widely used pieces of equipment in the Hong Kong sea-freight container yards. Workload distribution in the yard changes continuously over time. The dynamic deployment of RTGCs is an important issue in yard operation management. This paper investigates the dynamic crane deployment problem with the objective of determining the crane deployment frequency and routes over a planning horizon to minimize the total workload overflow. The problem is formulated as a mixed integer programming model. A heuristic algorithm is then developed to solve problems of practical sizes. The heuristic quickly finds a near optimal solution for crane deployment operation.

Dynamic crane deployment in container storage yards

Storage yards at container terminals serve as temporary buffers for inbound and outbound containers. Rubber tyred gantry cranes (RTGCs) are the most frequently used equipment in yards for container handling. The efficiency of yard operations heavily depends on the productivity of these RTGCs. As the workload distribution in the yard changes over time, dynamic deployment of RTGCs among storage blocks (container stacking areas) is an important issue of terminal operations management. This paper addresses the crane deployment problem. Given the forecasted workload of each block in each period of a day, the objective is to find the times and routes of crane movements among blocks so that the total delayed workload in the yard is minimized. The problem is formulated as a mixed integer programming (MIP) model and solved by Lagrangean relaxation. To improve the performance of this approach, we augment the Lagrangean relaxation model by adding additional constraints and modify the solution procedure accordingly. Computational experiments show that the modified Lagrangean relaxation method generates excellent solutions in short time.

Interblock Crane Deployment in Container Terminals

We consider the problem of scheduling the movements of cranes in a container storage yard so as to minimize the total unfinished workload at the end of each time period. The problem is formulated as a mixed-integer linear program, and the computational complexity ofthe problem is analyzed. A Lagrangian decomposition solution procedure is described. A new solution approach, called the successive piecewise-linear approximation method, is also developed. Through computational experiments, we show that our proposed solution methods are both efficient and effective for large-sized problems.