Moreover, we propose a method for obtaining every possible simulation result of DES models when feeding them events with uncertainty quantification on their time component. Discrete Event Simulation (DES) can better characterize randomness and should be part of every project’s toolkit in order to assess the effects of design variability. The only time the state changes in a discrete event simulation is when an event occurs.
This thesis proposes data types for handling representation of time properly in DES, including irrational and periodic time values. Any and every performance metric is a function of the models state. However, sometimes, answering a question requires evaluating the results of all values in the uncertainty interval. When collecting data using metrological instruments and procedures, the measurement results include uncertainty quantifications, usually defined as intervals. In this chapter, we will also learn about. The model used in a discrete system simulation has a set of numbers to represent the state of the system, called as a state descriptor. In addition, it is common to collect data from real systems to predict future phenomena, for example for weather forecasting. In discrete systems, the changes in the system state are discontinuous and each change in the state of the system is called an event. The approximation of time values in the simulation can affect the time-line preventing the generation of correct results.
DISCRETE EVENT SIMULATION SIMULATOR
Opposite is the case of time variables simulator has to interact actively with them for reproducing the chronology of events over R+, which is usually represented by approximated data types as floating-point. The message data type is usually defined as part of the model and the simulator algorithms do not operate with them. In computer implementations, an event could be represented by a message, and a time occurrence. The technique is called ”discrete-event” because the processing of each event of the chronology takes place at discrete points of a continuous time-line. Discrete-Event Simulation (DES) is a technique in which the simulation engine plays a history following a chronology of events.
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