The increased software robustness and the highly reduced costs in coding any application problem compensate, however, for the sacrifice of efficiency in executing a particular simulation project. Although many problems of numerical mathematics and information processing which are discussed in this thesis had to be considered and solved, the approach to them has been from the viewpoint of an engineer rather than from that of a mathematician. Combined system simulation as it is described in this thesis is a relatively new technique for the simulation of a class of systems having properties suitable to both continuous system simulation and discrete event simulation , two techniques well known to the simulation community. This combined technique has first been proposed by Fahrland. Major techniques and methodologies involved in this simulation approach are surveyed.
Special aspects considered are numerical behavior and information processing.
It is shown that this technique is applicable to a much larger class of problems than originally suggested by Fahrland. Simulation techniques are a very broad topic. The subject dealt with in this thesis covers many facets - numerical analysis, ordinary and partial differential equations, formal languages, and software design. Since most readers will have the level of familiarity required with only some of these facets, the thesis tries to provide the reader with all the information necessary for understanding the numerical and information processing aspects involved. However, a basic knowledge of continuous system modeling and discrete event modeling are a prerequisite to the understanding of this thesis.