Simulation

Abstract

Simulation is one of the most powerful tools available to decision-makers responsible for the design and operation of complex processes and systems. T)\e purpose of this paper is to discuss the concept and approach of simulation as a problem solving tool. Simulation involves building a mathematical model that attempts 10 describe a real world situation. The goal of the model is to incorporate important variables and their interrelationships in such a way that we can study the impact of managerial changes upon the total system. The approach has many advantages over other management science techniques and is especially useful when a problem is too complex or difficult to be solved by other means. Simulation is a procedure in which random numbers are generated according to probabilities assumed to be associated with a source of uncertainty. Outcomes associated with these random drawings are then analysed to determine the likely results and the associated risk. This technique is oftentimes called Monte Carlo simulation, being named for the city of Monte Carlo. The Monte Carlo method, as it is understood today, encompasses any technique of statistical sampling employed to approximate solutions to quantitative problems. The Monte Carlo method 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. Monte Carlo simulation is illustrated by hands on problems of inventory, queuing and machine maintenance. Many of the applications of simulation are in the areas of education and training, military, medical, manufacturing, entertainment, and many others.