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Abstract

Timm and Lorig 2 EVOLUTION OF COMPUTER SIMULATION Almost 70 years ago, the foundation for computer simulation has been laid. Back then the invention of ENIAC (a "general purpose electronic computing machine" (Goldstine and Goldstine 1946) developed for calculating fire tables during World War II) enabled scientists to automatically execute mathematical computations for solving numerical problems (Ulam 1990). Since then, hardware for executing simulation experiments has been enhanced and the application areas expanded. Nowadays, computer simulation is applied in various disciplines and has become an essential technique in scientific research. By observing and adjusting simulation models, hypotheses concerning the behavior of artificial systems can be evaluated and the impacts of modifying real systems can be estimated ex ante (Banks 1998). However, findings made by analyzing artificial systems are often used for drawing conclusions in regard to the real world. Especially in the context of investment decisions, simulation is frequently used for purposes of planning alternative approaches. Common areas of application are, for example, factory planning including materialflow simulation (e.g. Kühn 2006) or traffic simulation when building new road networks or redesigning traffic junctions (e.g. Lattner et al. 2011). Therefore, the necessity of general conditions and guidelines for assuring a certain level of quality is obvious. Reliable results can only be generated if the preparation and execution of simulation experiments are conducted under well-defined or even standardized conditions. Only in this case, results may be used as a profound basis for decision-making or as an origin for further research. Since the beginnings of simulation research, numerous articles have been published discussing the classification and application of the technology. In this regard, various approaches describing conditions for conducting simulation studies have been proposed as well. Furthermore, the definition of the term computer simulation itself is varying in literature. Humphreys compared partially opposing definitions and derived the following definition: "A computer simulation is any computer-implemented method for exploring the properties of mathematical models where analytic methods are unavailable." (Humphreys 1990) In contrast, Banks developed another commonly used definition of the term computer simulation: "A simulation is the imitation of the operation of a real-world process or system over time." (Banks 1996) The definitions mentioned above emphasize the ambiguity in the understanding of the technology. Computer simulation can either be regarded as a method (e.g. for the generation of knowledge (Ören 1987)) or a tool (e.g. for generating artificial scenarios by imitating real systems (Reynolds 2008)). Yet, when performing simulation experiments, most of the authors do not seem to be aware of this fundamental methodological uncertainty. Accordingly, a proper application of computer simulation is difficult.