Inventory-based dispatching of automated guided vehicles on container terminals

This paper deals with automated guided vehicles (AGVs) which transport containers between the quay and the stack on automated container terminals. The focus is on the assignment of transportation jobs to AGVs within a terminal control system operating in real time. First, we describe a rather common problem formulation based on due times for the jobs and solve this problem both with a greedy priority rule based heuristic and with an exact algorithm. Subsequently, we present an alternative formulation of the assignment problem, which does not include due times. This formulation is based on a rough analogy to inventory management and is solved using an exact algorithm. The idea behind this alternative formulation is to avoid estimates of driving times, completion times, due times, and tardiness because such estimates are often highly unreliable in practice and do not allow for accurate planning. By means of simulation, we then analyze the different approaches. We show that the inventory-based model leads to better productivity on the terminal than the due-time-based formulation.     

Strategies for dispatching AGVs at automated seaport container terminals

Control of logistics operations at container terminals is an extremely complex task, especially if automated guided vehicles (AGVs) are employed. In AGV dispatching, the stochastic nature of the handling systems must be taken into account. For instance, handling times of quay and stacking cranes as well as release times of transportation orders are not exactly known in advance. We present a simulation study of AGV dispatching strategies in a seaport container terminal, where AGVs can be used in single or dual-carrier mode. The latter allows transporting two small-sized (20 ft) or one large-sized (40 ft) container at a time, while in single-mode only one container is loaded onto the AGV irrespective of the size of the container. In our investigation, a typical on-line dispatching strategy adopted from flexible manufacturing systems is compared with a more sophisticated, pattern-based off-line heuristic. The performance of the dispatching strategies is evaluated using a scalable simulation model. The design of the experimental study reflects conditions which are typical of a real automated terminal environment. Major experimental factors are the size of the terminal and the degree of stochastic variations. Results of the simulation study reveal that the pattern-based off-line heuristic proposed by the authors clearly outperforms its on-line counterpart. For the most realistic scenario investigated, a deviation from a lower bound of less than 5% is achieved when the dual-load capability of the AGVs is utilized.     

Deadlock handling for real-time control of AGVs at automated container terminals

In automated container terminals, situations occur where quay cranes, stacking cranes, and automated guided vehicles (AGVs), directly or indirectly request each other to start a specific process. Hence, all of the affected resources are blocked, possibly leading to the complete deadlock of individual cranes or AGVs. Particularly, AGVs are liable to deadlocks because they always need a secondary resource, either a quay crane or a stacking crane, to perform the pick-up and drop-off operations. Because usually no buffering of containers takes place at the interfaces between AGVs and cranes, the consequences of deadlocks are rather severe. Two different methods for the detection of deadlocks are presented. One is based on a matrix representation of the terminal system. The other directly traces the requests for the individual resources. To resolve deadlock situations arising in an automated container terminal, three different procedures are proposed. These procedures aim to modify the sequence of handling operations or to assign them to alternative resources so that conflicts between concurrent processes are resolved. The suitability of the concept is demonstrated in an extensive simulation study.     

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