Page 66 - DCAP208_Management Support Systems

Unit 5: Modeling and Analysis

Simulation is a technique for conducting experiments. Notes
Simulation is a descriptive method – there is no automatic search for an optimal solution.
A simulation model describes or predicts the characteristics of a given system under
different conditions.
The simulation process usually repeats an experiment many times to obtain an estimate
(and a variance) of the overall effect of certain action.

Simulation is used when the problem is too complex to be treated using numerical
optimization techniques.

5.5.2 Advantages of Simulation

Advantages of simulation are as follows:

The theory is fairly straightforward.
A great amount of time compression can be attained.
Simulation is descriptive – allows the manager to pose what-if questions → trial-and-
error approach to problem solving and can do so faster, at less expense, more accurately,
and with less risk.

The model is built from the manager’s perspective.
The simulation model is built for one particular problem and typically cannot solve any
other problem – every component in the model corresponds to part of the real system.

Simulation is often the only DSS modeling method that can readily handle relatively
unstructured problems.

5.5.3 Disadvantages of Simulation

Disadvantages of simulation are as follows:
The optimal solution cannot be guaranteed, but relatively good ones are generally found.

Simulation model construction can be a slow and costly process, although newer modeling
systems are easier to use than ever.
Solutions and inferences from a simulation study are usually not transferable to other
problems because the model incorporates unique problem factors.
Simulation is sometimes so easy to explain to managers that analytic methods are often
overlooked.

Simulation software sometimes requires special skills because of the complexity of the
formal solution method.

5.5.4 Methodology of Simulation

Simulation involves setting up a model of a real system and conducting repetitive experiments
on it. The methodology consists of the following steps:
1. Define the problem: We examine and classify the real-world problem – we specify why a
simulation approach is appropriate.
2. Construct the simulation model: This step involves determination of the variables and
their relationships, as well as data gathering.

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