Introduction to discrete event systems pdf download

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Downloaded over 12,000 times since it launched! Please also note that we are currently working on an expanded, second edition of this book. This contrasts with continuous simulation in which the simulation continuously tracks the system dynamics over time. In this approach, the first phase is to jump to the next chronological event.

A common exercise in learning how to build discrete-event simulations is to model a queue, such as customers arriving at a bank to be served by a teller. In this example, the system entities are Customer-queue and Tellers. The system events are Customer-Arrival and Customer-Departure. The event of Teller-Begins-Service can be part of the logic of the arrival and departure events.

A system state is a set of variables that captures the salient properties of the system to be studied. The simulation must keep track of the current simulation time, in whatever measurement units are suitable for the system being modeled. The simulation maintains at least one list of simulation events. This is sometimes called the pending event set because it lists events that are pending as a result of previously simulated event but have yet to be simulated themselves.

An event is described by the time at which it occurs and a type, indicating the code that will be used to simulate that event. When events are instantaneous, activities that extend over time are modeled as sequences of events. Some simulation frameworks allow the time of an event to be specified as an interval, giving the start time and the end time of each event. Single-threaded simulation engines based on instantaneous events have just one current event. In contrast, multi-threaded simulation engines and simulation engines supporting an interval-based event model may have multiple current events. In both cases, there are significant problems with synchronization between current events.