Jaap A. Ottjes

Comparing transportation systems for inter-terminal transport at the Maasvlakte container terminals

In this paper, a comparison between three transportation systems for the overland transport of containers between container terminals is presented. A simulation model has been developed to assist in this respect. Transport in this study can be done by either multi-trailers, automated guided vehicles or automated lifting vehicles. The model is equipped with a rule-based control system as well as an advanced planning algorithm. The model is applied to a realistic scenario for the Maasvlakte situation in the near future. The experiments give insight into the importance of the different characteristics of the transport systems and their interaction with the handling equipment. Finally, a cost analysis has been executed to support management investment decisions.

Simulation of a multiterminal system for container handling

A generic simulation model structure for the design and evaluation of multiterminal systems for container handling is proposed. A model is constructed by combining three basic functions: transport, transfer, and stacking. It can be used for further detailing of the subsystems in the terminal complex while preserving the container flow patterns in the system. The modeling approach has been applied to the complete set of existing and future terminals in the Rotterdam port area, using forecasts of containers flows, statistical data from existing terminals, expert opinions, and conceptual designs of the new port area called “second Maasvlakte”. Experimental results including the requirements for deep-sea quay lengths, storage capacities, and equipment for interterminal transport are shown. Further traffic flows on the terminal infrastructure are determined, and the consequences of applying security scanning of containers are evaluated.

Comparison of routing strategies for AGV systems using simulation

In automated transport systems, the origin-destination combinations are normally connected through a fixed layout, not representing the shortest path. The flexibility of these systems is limited and often the infrastructure is not optimally used. With the introduction of more powerful onboard computers and advanced sensor technology, the positioning and navigating possibilities of AGVs increased. However the routes, although virtual, are still fixed. A new step ahead would be to determine each path dynamically. This would use the free ranging capacities of AGVs to its full potential. In this paper, the benefits of the dynamic free ranging approach are investigated; a simulation model on the strategic level is presented that compares several common fixed layouts with the shortest connection approach. Naturally, the avoidance of collisions plays a central role. It is concluded that dynamic free ranging has high potential in terms of transport capacity of the resulting system

The application of distributed simulation in TOMAS: redesigning a complex transportation model

This paper describes the application of distributed discrete event simulation in the study of an automated container terminal. The new model was developed to continue the study of large and complex logistic systems. In a previous study, a standalone model of the terminal was used that included all the characteristics of container handling between the ships and the container stack. A new distributed simulation model was developed by decomposing the original model into a distributed structure of communicating, small sub models. It is shown that with relatively little effort and hardly any programming overhead, a complex standalone model can be decomposed into small, easy to understand sub models. The new distributed structure improves the transparency and maintainability of the simulation model, while guaranteeing the original benefits of the standalone model and the required reproducibility of the experiments.

New Developments in Airport Baggage Handling Systems

Abstract In this paper, new concepts for baggage transport to and from narrow-body aircraft are presented. Current baggage transport is labor intensive and bears the risk of damaging or losing bags. Moreover, it is time-critical because of tight flight schedules. An alternative transport and scheduling method, as well as the application of a prototype of a partly automated baggage loading and unloading vehicle (baggage truck) have been investigated using simulation, and this is reported in the first part of the paper. It appears that considerable savings are possible when using both the scheduling method and the new baggage vehicle. An increased security level is also to be expected. The prototype baggage truck has been further developed into a swap-body concept; this is presented in the second part of the paper.

Simulation-based determination of the required stockyard size for dry bulk terminals

Abstract This paper provides a methodology, supported with a simulation tool, to determine the required stockyard size for dry bulk terminals. To determine the parameters that affect the required storage size, the storage factor was derived analytically. This factor defines the ratio between the annual throughput of a dry bulk terminal and the required stockyard size. Simulation is required for stockyard dimensioning when including the stochastic variations in the ship interarrival times, ship sizes and bulk material storage times. In addition, operational procedures were investigated that potentially increase the storage capacity. In a case study, the proposed approach was demonstrated by sizing the required stockyard area for a specific import terminal.

Distributed intelligence in autonomous multi-vehicle systems

To make better use of existing infrastructures, new control methods are under development. In the Intelligent Infrastructures programme, an infrastructure is seen as a multi-agent system, with more or less autonomous subsystems that are related to each other in hierarchical, coordinated, cooperative, or non-cooperative way. Current controls for multi-vehicle systems are based on the hierarchical control concept. In this paper, it is shown how the incident handling, efficiency, and flexibility of multi-vehicle systems can be improved by applying a cooperative control strategy. An existing multi AGV application in a seaport illustrates that efficiency of operations can be improved considerably with smarter control. Finally, a research project is introduced concerning cooperative multi-agent control of true free-ranging automated guided vehicles.

Developing an AGV motion controller using simulation, emulation and prototyping

Today transport systems using automated guided vehicles (AGVs) are centrally controlled and use a fixed infrastructure. Substantial efforts are therefore necessary if expansion or a change in system layout is required. In addition, incidents cannot be handled as part of the common routine. To overcome these problems a distributed anticipatory control method for AGVs is called for. According to this method every AGV is made responsible for its own path planning and collision avoidance. This approach requires a highly accurate controller to enable the AGV to follow its planned trajectory. This paper describes the development and testing of a controller for both positional and speed control. The AGV is modelled as a simple system with two steering wheel axles and an electromotor. The theoretical results obtained by using Matlab, are compared with results from testing the controller using an emulation model. Finally, the controller is implemented on an actual vehicle prototype, scaled 1:25, representing an AGV used for sea-container transport. The results of this research can be used to develop a controller, which is capable of achieving the required accuracy for automated, large scale, container transport systems.

Intelligent infrastructures: distributed intelligence in transport system control - an illustrative example

The intelligent infrastructures research program aims at developing theory and applications concerning novel intelligent modes for control and management of the utilization of infrastructures, such as road, rail, energy, water and telecom. As an illustrative example of research topics within the scope of this program, distributed anticipatory control for automated guided vehicles is discussed. Today transport systems using automated guided vehicles (AGVs) are centrally controlled and use a fixed infrastructure. Substantial efforts are therefore necessary if expansion or a change in system layout is required. In addition, incidents cannot be handled as part of the common routine. To overcome these problems a distributed anticipatory control method for AGVs is called for. According to this method every AGV is made responsible for its own path planning and collision avoidance. A simulation model is set up to compare this method with the traditional, centrally controlled, method. In the paper preliminary results are shown and recommendations for further research are given.

Simulation-based rescheduling of the stacker–reclaimer operation

Abstract In this paper simulation is applied to reschedule the stacker–reclaimers operation to increase the dry bulk terminals performance by reducing the waiting time of cargo trains being loaded at the terminal. Stacker–reclaimers perform both the stacking and reclaiming of dry bulk materials. Due to the differences in loads between ships and cargo trains, the time needed for stacking and reclaiming varies considerably per job. The simulation tool developed can be used to support decisions when to interrupt ship servicing in favor of train loading based on the availability of transportation routes and expected disturbances. An experimental study demonstrated that ships and trains have to spend less time in the port when the stockyard lanes are accessible by two stacker–reclaimers due to the higher machines redundancy. Using the stacker–reclaimers rescheduling function the average port time of trains decreased without significantly affecting the port time of ships.