Knowledge-based modeling of discrete-event simulation systems

Modeling a simulation system requires a great deal of customization. At first sight no system seems to resemble exactly another system and every time a new model has to be designed the modeler has to start from scratch. The present simulation languages provide the modeler with powerful tools that greatly facilitate building models (modules for arrivals or servers, etc.). Yet, also with these tools the modeler constantly has the feeling that he is reinventing the wheel again and again. Maybe the model he is about to design already exists (maybe the modeler has designed it himself some time ago) or maybe a model already exists that sufficiently resembles the model to be designed. In this article an approach is discussed that deploys knowledge-based systems to help selecting a model from a database of existing models. Also, if the model is not present in the database, would it be possible to select a model that in some sense is close to the model that the modeler had in mind

A 3D simulation case study of airport air traffic handling

Modern Windows-based simulation packages bring simulation within reach of decision-makers. The use of graphics enables the manager to observe an animation of the simulated reality, to focus on the essentials of the model without the need to bother about implementation details. In most applications a 2D representation will satisfy the simulation objectives. One field of application in which 3D simulation is highly recommended is air traffic handling on and above an airport. In order to get a real understanding of this kind of process 3D simulation is indispensable. In this article a simulation is described in which 3D animation is essential to base management decisions on

An object-oriented model for strategic analysis

Strategic analysis is a domain in which human expertise and experience are key factors. This is the reason that attempts have been made to automate the strategic analysis by expert systems. This article means to capture the expert knowledge to be used in an expert system with the focus on an object-oriented model of the domain. Based on this OO model an expert system can be developed that is able to analyze a corporate enterprise with several Strategic Business Units each of which carrying more than one product at a time. Such an expert system would be able to analyze the various synergetic aspects

A Knowledge base representing Porter's Five Forces Model

Strategic Analysis and Planning is a field in which expertise and experience are key factors. In order to decide on strategic matters such as the competitive position of a company experts heavily lean on their ability to reason with uncertain or incomplete knowledge, or in other words on their experience and expertise. An important aspect is to assess a company's profit potential in the industry for which Porter's Competitive Forces Model is by far the most widely used framework. This article focuses on the various aspects of designing and developing an expert system representing Porter's Competitive Forces Model

Arrival processes in port modeling: insights from a case study

This paper investigates the impact of arrival processes on the ship handling process. Two types of arrival processes are considered: controlled and uncontrolled. Simulation results show that uncontrolled arrivals of ships perform worst in terms of both ship delays and required storage capacity. Stock-controlled arrivals perform best with regard to large vessel delays and storage capacity. The combination of stock-controlled arrivals for large vessels and equidistant arrivals for barges also performs better than the uncontrolled process. Careful allocation of ships to the mooring points of a jetty further improves the efficiency.supply chain management;logistics;simulation;transportation;case study

Implementation and results of a prototype expert system on strategic analysis

Expertise and experience are key factors for experts in strategic analysis in order to give advice on strategic matters such as the strength or the competitive position of an enterprise. They are able to reason with uncertain or incomplete knowledge. Expert systems may be able to do the same if this heuristic knowledge can be modeled and processed properly. This article discusses the modeling, implementation and the results of such an expert on strategic analysis. The results are compared to those generated by Business Insight and further improvements are discussed

Arrival processes in port modeling: insights from a case study

This paper investigates the impact of arrival processes on the ship handling process. Two types of arrival processes are considered: controlled and uncontrolled. Simulation results show that uncontrolled arrivals of ships perform worst in terms of both ship delays and required storage capacity. Stock-controlled arrivals perform best with regard to large vessel delays and storage capacity. The combination of stock-controlled arrivals for large vessels and equidistant arrivals for barges also performs better than the uncontrolled process. Careful allocation of ships to the mooring points of a jetty further improves the efficiency

On the effect of ship arrival processes on jetty and storage capacity

Ports provide jetty facilities for ships to load and unload their cargo. Jetty capacity is costly and therefore limited, causing delays for arriving ships. However, ship delays are also costly, so terminal operators attempt to minimize their number and duration. Here, simulation has proved to be a very suitable tool. However, in port simulation models, the impact of the arrival process of ships on the model outcomes tends to be underestimated. This report considers three arrival processes: stock-controlled, equidistant, and uncontrolled. We assess how their deployment in a port simulation model,based on data from a real case study, affects the efficiency of the loading and unloading process, making a case for careful modeling of arrival processes in port simulations. Uncontrolled, which is an assumed arrival process property in many client-oriented simulations, actually performs worst in terms of both ship delays and required storage capacity. Stock-controlled arrivals perform best with regard to large vessel delays and storage capacity. Additional control of the arrival process through the application of a priority scheme in processing ships further impacts efficiency in all three cases

Arrival Processes for Vessels in a Port Simulation

Ports provide jetty facilities for ships to load and unload their cargo. Jetty capacity is costly and therefore limited, causing delays for arriving ships. However, ship delays are also costly, so terminal operators attempt to min imize their number and duration. Here, simulation has proved to be a very suitable tool. However, in port simulation models, the impact of the arrival process of ships on the model outcomes tends to be underestimated. This report considers three arrival processes: stock-controlled, equidistant, and uncontrolled. We assess how their deployment in a port simulation model, based on data from a real case study, affects the efficiency of the loading and unloading process, making a case for careful modeling of arrival processes in port simulations. Uncontrolled, which is an assumed arrival process property in many client-oriented simulations, actually performs worst in terms of both ship delays and required storage capacity. Stock-controlled arrivals perform best with regard to large vessel delays and storage capacity. Additional control of the arrival process through the application of a priority scheme in processing ships further impacts efficiency in all three cases.Ports provide jetty facilities for ships to load and unload their cargo. Jetty capacity is costly and therefore limited, causing delays for arriving ships. However, ship delays are also costly, so terminal operators attempt to min imize their number and duration. Here, simulation has proved to be a very suitable tool. However, in port simulation models, the impact of the arrival process of ships on the model outcomes tends to be underestimated. This report considers three arrival processes: stock-controlled, equidistant, and uncontrolled. We assess how their deployment in a port simulation model, based on data from a real case study, affects the efficiency of the loading and unloading process, making a case for careful modeling of arrival processes in port simulations. Uncontrolled, which is an assumed arrival process property in many client-oriented simulations, actually performs worst in terms of both ship delays and required storage capacity. Stock-controlled arrivals perform best with regard to large vessel delays and storage capacity. Additional control of the arrival process through the application of a priority scheme in processing ships further impacts efficiency in all three cases