Discrete event simulation (DES) is the process of codifying the behavior of a complex system as an ordered sequence of well-defined events. In this context, an event comprises a specific change in the system's state at a specific point in time.
finite capacity scheduling
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Common applications of DES include stress testing, evaluating potential financial investments, and modeling procedures and processes in various industries, such as manufacturing and healthcare.
As an example of a situation that lends itself to DES, consider the amount of electrical power consumed by a corporation's office building as a function of time. Discrete events affecting this function include power-up or power-down of any electrical device in the building. Instantaneous changes of state in a device already powered-up are also discrete events; for example, a speed change in a cooling fan or a brightness change in a desk lamp.
An effective DES process must include, at a minimum, the following characteristics:
- Predetermined starting and ending points, which can be discrete events or instants in time.
- A method of keeping track of the time that has elapsed since the process began.
- A list of discrete events that have occurred since the process began.
- A list of discrete events pending or expected (if such events are known) until the process is expected to end.
- A graphical, statistical, or tabular record of the function for which DES is currently engaged.
DES is commonly used to monitor and predict the behavior of investments; the stock market is a classic example. DES can also help administrators predict how a network will behave under extraordinary conditions, such as the Internet during a major disaster.