Introduction to simulation languages



The purpose of this paper is to give a brief introduction to simulation languages. The paper contains a discussion on the hierarchy of computer languages and their relation to simulation, the advantages and disadvantages of using simulation languages, factors to consider when selecting a language, and some of the characteristics of the three most popular discrete simulation languages. A more thorough treatment of simulation languages and their use are contained in [2], [4], and [10]. A significant portion of the effort in any simulation study is in programming the model to run on a digital computer. This programming occurs after the model has been defined. The selection of the language should, in general, be done prior to developing the model to be programmed because (i) there must be a comptibility between how the system is modeled and the computer language used and (ii) some simulation languages aid in the modelling process. The language selected is usually a general purpose language (higher level language) or a simulation language.

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    ABSTRACT: Each discrete event simulation language incorporates a time control procedure to conduct timing management and next event selection. Each time control procedure embodies, and thus imposes, a strategy (approach, method) for next event selection- and thereby determines the world view of a language. The three generally recognized strategies are event scheduling, activity scanning and process interaction. This paper presents algorithmic formulations of the three strategies and their modeling routines, as well as detailed discussions and comparisons of the strategies. The algorithmic formulations serve to aid understanding by describing essential aspects of the strategies while excluding implementation details which are not strategy-dependent, and which tend to detract from the essential concepts. A significant practical application of the formulations is discussed. This consists of merging the algorithms for the event scheduling and process interaction strategies into one algorithm, which then served as a model for combining GPSS and GASP IV into a simulation system providing the individual capabilities of both language, and the capability to intermix GPSS and GASP within a single model.
    International Journal of Computer and Information Sciences 04/1982; 11(2):101-122. DOI:10.1007/BF00995526