Figure 72: Simulation: classical definitions

                     1964-1996

 

 

Defintions by:

Keith Douglas Tocher: The Art of Simulation. 1964.

John McLeod (Hrsg.): Simulation. The Dynamic Modeling of Ideas and Systems with Comupters. 1968.

Geoffrey Gordon: System Simulation. 1969.

Patrick Rivett: Principles of model building. The construction of models for decision analysis. 1972.

Robert E. Shannon: Systems Simulation. The art and science. 1975.

Rüdeger Baumann: Didaktik der Informatik. 1996.

Helmut Kohorst. 1996.

 

 

London: English Universities Press 1963; Princeton, NJ: Van Nostrand 1964.

 

Arthur Porter in the „General Editor’s Foreword“:

The present volume deals with the study of industrial operations and processes using large-scale data-processing and computer systems as simulators. It is perhaps the first book to be published on the subject.

 

 

New York: McGraw-Hill 1968.

 

John McLeod, p. 3

But unlike some others, McCoy made a strong recommendation: „Build plans on the simple definition that simulation ist he act of representing some aspects of the real world by numbers ors symbols which may be easily manipulated to faciliate their study ...“

 

Robert D. Brennan, p. 6

Simulation ist he development and use of models to aid in the evaluation of ideas and the study of dynamic systems or situations.

... This ..  suggests ... that a model will be taken to mean anything which resembles the simuland (that which is simulated) in all those aspects which are pertinent to the study of interest; the model need not, and generally does nit, resemble the simuland in another way.

Note that computers are not mentioned in our definition of Simulation. Computers are not necessary for simulation; it is just tthat they are the best tools so far available for the job.

 

 

Englewood Cliffs, N. J.: Prentice-Hall 1969; 2. Aufl. 1978.

dt.: Systemsimulation. München: Oldenbourg 1972.

 

p. 5

We define a model as the body of information about a system gathered for the purpose of studying the system. Since the purpose of the study will determine the nature of information that is gathered, there is no unique model of a system.

 

p. 17-18

Given a mathematical model of a system, it is sometimes possible to derive information about the system by analytic means ...  Where this is not possible, it is necessary to use numerical computation methods for solving the equations ... In the case of mathematical models, a particular technique that has come to be identified as system simulation ist one in which all equations of the model are solved simultaneously with steady increasing values of time.

We therefore define system simulation as the technique of solving problems by following the changes over time of a dynamic model of a system.

... Since the technique of simulation does not attempt to solve the equations of a model analytically, a mathematical model constructed for simulation purposes ist usually of a different nature than one constructed for analytic techniques ... Typically, it is built in a series of sections corresponding to the block diagram method ... Each section can be described mathematically in a straight forward and natural manner without undue concern for the complexity introduced by having much such sections. The equations, however, must be constructed and organized in a way that enables a routine procedure to be used for solving them simultaneously.

... Simulation is ... essentially a experimental problem-solving technique. Many simulation runs have to be made to understand the relationships involved in the system, so the use of simulation in an study must be planned as a series of experiments.

 

 

London: Wiley 1972 (vgl. 1980);
dt.: Entscheidungsmodelle in Wirtschaft und Verwaltung. Frankfurt am Main: Herder & Herder 1974.

 

p. 109-110

Hence simulation was initially developed as a way of approaching problems for which no explict mathematical solution can be devised. However,as the method has developed it has been seen to be very powerful and to a certain extent it is now true that it is not the simulator who has to excuse himself for not using mathematics but rather the mathematician wo has to excuse himself for not using simulation.

In most problems where simulation is used there are two distinct phases. The first is  an understanding of the structure of the real situation in such a way that a simulation process can be deployed and the second phase is the derivation of sampling procedures by means of which the successive experiments, which lie at the heart of a simulation, can be performed.

There are in general three main reasons for using simulation.

The first of these has been referred to as the case where the technical problem, be it mathematical or statistical, is to complex to be solved.

The second field in which simulation is used covers those problems where the research worker needs to gain some understanding of a complex real situation and be able to manipulate it in an isomorphic form.

The third type of situation is that in which the researcher is dealing with problems which do not yet exist in the real world and where one has to anticipate in advance how one should deal with them should they arise.

 

 

Englewood Cliffs, NJ: Prentice-Hall 1975.

 

p. ix

Simulation is one of the most powerful analysis tools available tho those responsible for the design and operation of complex processes or systems. The concept of simulation is both simple and intuitively appealing. It allows the user to experiment with systems (real or proposed) where it would be impossible or impractical otherwise.

... Simulation modeling ist heavily based upon computer science, mathematics, probability, and statistics. Yet simulation modeling and experimentation remain very intuitive processes ... Since this poorly understood process is as much art as science, we offer few firm rules or fixed outlines.

 

p. 2

Simulation is the process of designing a model of a real system and conducting experiments with this model for the purpose either of understandig the behavior of the system or of evaluating various strategies (within the limits imposed by a criterion or a set of criteria) for the operation of the system. Thus we understand the process of simulation to include both the construction of the model and the analytical use of the model for studying a problem.

By a model of a real system we mean a representation of a group of objects or ideas in some form other than of the entity itself, and here the term „real“ is used in the sense of „in existence or capable of brought into existence“. Thus systems in the preliminary or planning stage can be modeled as well as those already in existence.

 

 

1996 Definitions

 

Stuttgart: Klett Schulbuchverlag 1990; 2. neubearbeitete Aufl. 1996.

 

Since „simulation“ is often used in the context of  model construction. Rüdeger Baumann (1996) quotes the VDI guideline 3633:

" Simulation means imitating a system with his dynamic processes by a model we can experiment with to get knowledge appliable to reality."

Then Baumann critizises this definition, stating more pecisely that not the system is imitated but only the behavior of a modeled system. The imitation of a system is not called simulation but modeling.

If computers are used for the necessary calculations, one speaks of a computer simulation. For that the model has to be prepared in mathematical-logical form, i. e. quantitatively formulated and translated in a computer program.

 

 

 

By simulation we understand the process of elaborating a prediction with the help of  experimentation within the model level, i. e. to realise "trials" or "calculations" in an abstract model of a system. The purpose of a simulation is the analysis of the (future) system behavior.