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Modelling and Simulation PDF 17.6 MBUpdated 23 Oct 2026
Handout CS620 Complete Handouts by VUBuddy PDF 17.6 MB
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CS620 Modelling and Simulation
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CS620 Modeling & Simulation

Handouts Organized by Scammer404

Module – 1

Modeling & Simulation is an extremely important part of our daily lives. Our entire living experience is based on the concept of “Consciousness” The state of being aware of and responsive to one's surroundings

Module – 2

Analysis of Complex Systems:

  • Simulation enables the study of, and experimentation with, the internal interactions of a complex system or of a subsystem within a complex system.

Defining Changes:

  • Informational, organizational, and environmental changes can be simulated, and the effect of these alterations on the model's behavior can be observed.

Knowledge from Simulation:

The knowledge gained during the designing of a simulation model could be of great value toward suggesting improvement in the system under investigation.

Learning from Change:

Changing simulation inputs and observing the resulting outputs can produce valuable insight into which variables are the most important and into how variables interact.

Pedagogical Value:

Simulation can be used as a pedagogical device to reinforce analytic solution methodologies.

Trial & Error:

Simulation can be used to experiment with new designs or policies before implementation, so as to prepare for what might happen.

Verification of Mathematical Models:

Simulation can be used to verify analytic solutions.

Learning Requirements for a Machine:

Simulating different capabilities for a machine can help determine the requirements on it.

Replacement for Training:

  • Simulation models designed for training make learning possible without the cost and disruption of on-the-job instruction.

Animation of Simulation:

Animation shows a system in simulated operation so that the plan can be visualized.

Visually Understanding Modern Factories:

The modem system (factory, wafer fabrication plant, service organization, etc.) is so complex that its internal interactions can be treated only through simulation.

Other reasons!

Explain (very distinct from predict) Guide data collection Illuminate core dynamics Suggest dynamical analogies Discover new questions Promote a scientific habit of mind Bound (bracket) outcomes to plausible ranges Illuminate core uncertainties. Offer crisis options in near-real time Demonstrate tradeoffs / suggest efficiencies Challenge the robustness of prevailing theory through perturbations Expose prevailing wisdom as incompatible with available data Train practitioners Discipline the policy dialogue Educate the general public Reveal the apparently simple (complex) to be complex (simple)

Module – 3

Simulation: When isn’t an Appropriate Tool?

There is a typical misconception often in graduate students that everything can be, or should be simulated. Simulation is NOT for everything!

Banks and Gibson (1997):

Banks and Gibson present ten rules for evaluating when simulation is not appropriate

Rule Number 1:

  • Simulation should not be used when the problem can be solved by common sense.

Example:

E.g. In an automobile tag facility serving customers who arrive randomly at an average rate of 100/hour and are served at a mean rate of 12/hour. To determine the minimum number of servers needed, simulation is not necessary. Just compute 100/12 = 8.33 indicating that nine or more servers are needed.

Rule Number 2:

  • Simulation should not be used if the problem can be solved analytically.
  • For example, under certain conditions, the average waiting time in the example above can be found from curves that were developed by Hillier and Lieberman [2002].

Rule Number 3:

Simulation should not be used if it is easier to perform direct experiments.

Example:

In a fast-food drive-in restaurant it can be less expensive to stage a person taking orders using a hand-held terminal and voice communication to determine the effect of adding another order station on customer waiting time.

Rule Number 4:

Don’t use simulation if the costs exceed the savings. If a simulation study costs $20,000 and the savings might be $10,000, simulation would not be appropriate.

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