Simulation Techniques in Operations Research—A Review

The purpose of this paper is to give an introductory account of the techniques of simulation, to present a few of the leading ideas which have been developed, and to draw attention to what is in fact a very open and somewhat ill-defined subject.

Considerable confusion exists over the best terminology to use. The term ‘Monte Carlo’ is presently somewhat fashionable, the term ‘simulation’ is to be preferred, because it does not suggest that the technique is limited to what is familiar to statisticians as a sampling experiment.

By simulation is meant the technique of setting up a stochastic model of a real situation, and then performing sampling experiments upon the model. The feature which distinguishes a simulation from a mere sampling experiment in the classical sense is that of the stochastic model. Whereas a classical sampling experiment in statistics is most often performed directly upon raw data, a simulation entails first of all the construction of an abstract model of the system to be studied.