Der Begriff Diskrete Ereignis-Simulation (DES), auch "Ereignis-orientierte Simulation" genannt, wurde als ein Oberbegriff etabliert, der verschiedene Arten von Computersimulations-Methoden subsumiert, die alle auf der allgemeinen Idee basieren, ein Computermodell eines als diskretes dynamisches System aufgefassten realen Systems zu gewinnen, indem die Zustandstruktur des Systems mit Hilfe von Zustandsvariablen und seine Dynamik mit Hilfe von zustandsverändernden Ereignissen modelliert wird.

Es gibt jedoch keine allgemein akzeptierte Definition von DES. Vielmehr gibt es eine Anzahl von unterschiedlichen DES-Formalismen (wie z.B. Petri-Netze, State Charts, Ereignis-Graphen oder DEVS) und es gibt unterschiedliche DES-Werkzeuge/-Frameworks. Viele von ihnen (wie z.B. Arena, Simio und AnyLogic) basieren auf dem Paradigma von Verarbeitungsnetzwerken, bzw. Processing Networks (PN), bei dem Verarbeitungsobjekte ein System (an einem Eingangsknoten) betreten und dann zu einer Reihe von Verarbeitungsknoten weitergeleitet werden, wo sie Verarbeitungsaktivitäten unterworfen sind, die unter Zuhilfenahme von Ressourcen durchgeführt werden, bevor sie das System (an einem Ausgangsknoten) verlassen.

In einigen Lehrbüchern und Tutorien wird DES mit dem PN-Paradigma verwechselt. Das PN-Paradigma ist jedoch kein allgemeiner DES-Ansatz, weil es auf Probleme beschränkt ist, die in der Form von Verarbeitungsnetzwerken modelliert werden können, wie z.B. Produktionssysteme oder Dienstleistungsbetriebe. Aber viele andere diskrete Systeme, wie Lager-Systeme, Unternehmen, Märkte oder sozio-technische Systeme, wie Aufzüge oder Straßenverkehrssysteme, entsprechen nicht Verarbeitungsnetzwerken.

Beispiele von DES-Modellen mit ereignisbasierter Zeitprogression

Verarbeitungsnetzwerk-Modelle

ServiceDesk-4: A service desk is modeled as a processing node of a processing network that has an entry node and an exit node for arriving and departing customers.
ConsecutiveServices-2: The customers of the Department of Motor Vehicles first have to queue up at the reception for their request being recorded. Then they have to wait for a clerk who will handle their case. Both the reception desk and the case handling desk are modeled as processing nodes (with input queues) within a processing network that has an entry node and an exit node for arriving and departing customers.
FourConsecutiveMachines-3: A manufacturing company uses a linear assembly line with 4 consecutive machines. The simulation scenario defines an entry node for incoming orders, 4 consecutive processing nodes representing the four machines M1-M4, and an exit node.

Die folgenden beispielhaften Modelle basieren auf dem Objekt-Ereignis-Simulations-Paradigma (OES).

Lagerverwaltung: Ein Lagerverwaltungssystem mit einem kontinuierlichen Wiederbeschaffungsverfahren.
ServiceDesk-1: A queueing system model (one service and one queue) with two statistics: maximum queue length and service utilization. The model includes one object type: ServiceDesk, and two event types: CustomerArrival and CustomerDeparture, abstracting away from individual customers and from the composition of the queue, which is only represented in terms of its length.
ServiceDesk-2: A queueing system model (one service and one queue) with one statistic: the average length of time a customer spends in the system from arrival to departure. For recording their waiting times, individual customers need to be represented as entities/objects. The model includes two object types: ServiceDesk and Customer, and two event types: CustomerArrival and CustomerDeparture.
ServiceDesk-3: A queueing system model that models the service as an activity with the service desk as its resource, such that the service desk utilization statistics is computed automatically. The model includes one object type: ServiceDesk, one event type: CustomerArrival and one activity type: PerformService.
ConsecutiveServices: An activity-based model of two consecutive service desks with waiting lines. Both types of services are modeled as activity types, such that utilization statistics are computed automatically. The model includes one object type: ServiceDesk, one event type: CustomerArrival, and two activity types: Reception and CaseHandling.
DriveThru: A model of a drive through restaurant based on Introduction to Simulation by R.G. Ingalls, a tutorial given at the 2008 Winter Simulation Conference. The drive thru is modeled as a system with three order processing activities performed at service nodes with queues: the order taking at the menu board, the order preparation at the kitchen and the order pickup at the pickup window. The model includes four object types: MenuBoard, Kitchen, PickupWindow and Customer, one event type: CustomerArrival, and three activity types: OrderTaking, OrderPreparation and OrderPickup.
Lemonade Stand Game (Version 1): A Lemonade Stand as a manufacturing company that performs daily production based on demand forecasting.
Lemonade Stand Game (Version 2): A Lemonade Stand as a manufacturing company in a monoploy market dominated by weather conditions. This simulation example comes with an observation user interface (UI) that provides a visualization of simulation runs and with a user interaction UI that allows to play with the simulation.
The MIT Beer Game: (coming soon)
Lengnick's Baseline Economy: Lengnick's Baseline Economy consists of two types of economic actors only: households playing the roles of employees and consumers, and firms playing the roles of employers and producers. All firms produce and sell the same abstract consumption good that is bought (and consumed) by households. The numbers of households and firms are fixed (there is neither population growth nor shrinkage). Households do not die by starvation. When their income shrinks, they adapt by cutting their consumption. Firms do not get bankrupt. When their liquidity shrinks, they adapt by cutting wages. Consumption goods are produced and bought daily while labor is bought monthly. Households buy consumption goods only from a limited number of firms, their preferred suppliers, which they update continuously. Consumption expenditure increases with personal wealth, but at a decaying rate. Households are employed by at most one firm, their employer. They continuously search for an employer that pays a higher wage.