Page 249 - DCAP601_SIMULATION_AND_MODELING

Unit 13: Simulation Languages (I)

Notes
Figure 13.4: Stages used in Discrete Event Simulation

Key Principles

Although, discrete event simulation could conceivably be carried out by hand it can be
computationally intensive, therefore will invariably involve computers and software. The
software could be a high level programming language such as Pascal or a specialised event/data
driven application, such as iBright Ltd’s ‘baseSim’ (Monte Carlo Simulation). The five key features
found in the software simulation model are:

1. Entities: Representations of real-life elements e.g. in manufacturing these could be parts
or machines.
2. Relationships: Link entities together e.g. a part may be processed by a machine.

3. Simulation Executive: Responsible for controlling the time advance and executing discrete
events.
4. Random Number Generator: Helps to simulate different data coming into the simulation
model. Important that the random data can be reproduced in different simulation runs.
5. Results & Statistics: Important in validating the model and for providing performance
measures.

The simulation executive may operate in one of two manners [Ball, 1996]:
1. Time Slicing: Advances the model by a fixed amount each time, regardless of the absence
of any events to carry out.

2. Next Event: Advances the model to the next event to be executed, regardless of the time
interval. This method is more efficient than Time Slicing, especially where events are
infrequent, but can be confusing when being represented graphically

Notes Processes that take different times will appear to happen in the same time frame if
the stop event is the next event after the start event.

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