Introduction to Discrete-Event Simulation

Abstract

Consider simulation of some system which evolves through time. There is a huge variety of such applications. One can simulate a weather system, for instance. A key point, though, is that in that setting, the events being simulated would be continuous, meaning for example that if we were to graph temperature against time, the curve would be continuous, no breaks. By contrast, suppose we simulate the operation of a warehouse. Purchase orders come in and are filled, reducing inventory, but inventory is replenished from time to time. Here a typical variable would be the inventory itself, i.e. the number of items currently in stock for a given product. If we were to graph that number against time, we would get what mathematicians call a step function, i.e. a set of flat line seg- ments with breaks between them. The events here—decreases and increases in the inventory—are discrete variables, not continuous ones. DES involves simulating such systems.