The purpose of this chapter is to discuss the concept and approach of simulation as a problem-solving tool. Simulation involves building a mathematical model that attempts to describe a real-world situation. The model’s goal is to incorporate important variables and their interrelationships in such a way that we can study the impact of managerial changes on the total system. The approach has many advantages over other quantitative analysis techniques and is especially useful when a problem is too complex or difficult to solve by other means.

The Monte Carlo method of simulation is developed through the use of probability distributions and random numbers. Random number intervals are established to represent possible outcomes for each probabilistic variable in the model. Random numbers are then either selected from a random number table or generated by computer to simulate variable outcomes. The simulation procedure is conducted for many time periods to evaluate the long-term impact of each policy value being studied. Monte Carlo simulation by hand is illustrated on problems of inventory control, queuing, and machine maintenance.

Operational gaming and systems simulation, two other categories of simulation, are also presented in this chapter. The chapter concludes with a discussion of the important role of the computer in the simulation process.