Toward the development and implementation of object-oriented extensions for discrete-event simulation in a strongly-typed procedural language

The primary emphasis of this research is computer simulation. Computer simulations are used to model and analyze systems. To date, computer simulations have almost exclusively been written in procedural, strongly-typed languages such as FORTRAN or Pascal;Recent advancements in simulation research suggest an object-oriented approach to simulation languages may provide key benefits in computer simulation. The goal of this research is to combine the advantages of a simulation language written in a procedural, strongly-typed language with the benefits available through the object-oriented programming paradigm;This research presents a review of the methods of computer simulation. A significant portion of this research is devoted to a description of the development of the object-oriented simulation software in a strongly-typed, procedural language;The software developed in this research is capable of simulating systems with multiple servers and queues. Arrival and service distributions may be selected from the uniform, exponential, and normal family of distributions. Resource usage is not supported in the simulation program

Development of a standard framework for manufacturing simulators

Discrete event simulation is now a well established modelling and experimental technique for the analysis of manufacturing systems. Since it was first employed as a technique, much of the research and commercial developments in the field have been concerned with improving the considerable task of model specification in order to improve productivity and reduce the level of modelling and programming expertise required. The main areas of research have been the development of modelling structures to bring modularity in program development, incorporating such structures in simulation software systems which would alleviate some of the programming burden, and the use of automatic programming systems to develop interfaces that would raise the model specification to a higher level of abstraction. A more recent development in the field has been the advent of a new generation of software, often referred to as manufacturing simulators, which have incorporated extensive manufacturing system domain knowledge in the model specification interface. Many manufacturing simulators are now commercially available, but their development has not been based on any common standard. This is evident in the differences that exist between their interfaces, internal data representation methods and modelling capabilities. The lack of a standard makes it impossible to reuse any part of a model when a user finds it necessary to move from one simulator to another. In such cases, not only a new modelling language has to be learnt but also the complete model has to be developed again requiring considerable time and effort. The motivation for the research was the need for the development of a standard that is necessary to improve reusability of models and is the first step towards interchangability of such models. A standard framework for manufacturing simulators has been developed. It consists of a data model that is independent of any simulator, and a translation module for converting model specification data into the internal data representation of manufacturing simulators; the translators are application specific, but the methodology is common and illustrated for three popular simulators. The data model provides for a minimum common model data specification which is based on an extensive analysis of existing simulators. It uses dialogues for interface and the frame knowledge representation method for modular storage of data. The translation methodology uses production rules for data mapping

Semantic modelling for discrete event simulation.

Discrete event simulation modelling has been established as an important tool for management planning. This process has been aided by the availability of off-the-shelf simulation systems for microcomputers. Traditionally these have had text-based interfaces and very limited graphics. As the availability of powerful colour microcomputers have increased, graphical front-ends have been added. As clients have got used to consistent graphical interfaces (e.g. Apple Macintosh or Microsoft Windows), they have desired the same level of integration in their simulation support environments. Research in other fields has been utilised in improving simulation environments. These fields include relational databases, expert systems, formal languages and graphical environments. This thesis examines the use of artificial intelligence in the discrete event simulation field with the aim of examining some potential areas in which it might be possible to improve simulation environments. Existing simulation research in the artificial intelligence (AI) field is extended by investigating the graphical AI knowledge-base called semantic networks. This thesis demonstrates semantic modelling, a discrete event simulation modelling approach based on semantic networks, which attempts to give a consistent graphical interface throughout the life cycle of a simulation study. The semantic modelling approach also incorporates expert system and natural language research. A prototype system of this approach is described

Development of an Integrative Structure for Discrete Event Simulation, Object Oriented Modeling and Embedded Decision Procession

Industrial Engineering and Managemen

Enhancing discrete event modelling by interfacing expert systems and simulation models.

This thesis investigates the representation of operational decision makers within simulation modelling. Artificial Intelligence concepts, such as expert systems focus on the problem of representing, in high-level code, complex real-world decision making problems. The author therefore proposes that the use of expert system technology may provide an improved means of representing operational decision tasks and that as a consequence, apriori possibilities may exist in the context of model experimentation based on alternative operational policies. The thesis further investigates the nature of operational decision making and the potential need to represent within a model, inter-dependencies between decision makers. A prototype system called ESSIM is developed which comprises of two interlinked components, a discrete event simulation module and expert system module. The benefits of the proposed approach are then assessed by comparing the functionally of ESSIM with conventional modelling techniques. The comparison is carried out by developing three alternative models of an automated container port, one of these using ESSIM. Experiments were then devised and executed which seek to draw conclusions on the thesis proposal