Advantages of Modeling and Simulations Quiz

Models and Simulations

• A model is an abstraction of a system, used to understand and represent the system in a comprehensible way.
• Models can have many forms, including mathematical equations, diagrams, and physical mock-ups, depending on the purpose of the model.
• A model is a static representation of the system, while a simulation uses a model to emulate the dynamic characteristics of the system.

Simulations

• A simulation is an execution of a model, and its quality depends on the quality of the model.
• Simulations are used instead of real systems for many reasons, including:
  • Being cheaper
  • Being more configurable and controllable
  • Being safer
  • Being faster (or slower)
  • Being more accessible for data collection

Computer Simulation

• Computer simulation is ideal when a model can be expressed in terms of mathematics and logic.
• Computer simulations can easily store information about all attributes of the model throughout the simulation run.
• Steps involved in creating simulations include:
  • Gathering and preparing accurate data
  • Creating mathematical formulas (algorithms) to output data
  • Generating animations, graphs, or other output displays
  • Verifying and validating the data through re-testing

Systems

• A system is a part of some potential reality where we are concerned with space-time effects and casual relationships among parts of the system.
• Defining a system requires setting boundaries to separate it from the rest of the universe.
• Examples of systems include:
  • Energy flow among biological components in a pond
  • Physical motion of balls rebounding inside a closed space
  • Customer service at a fast-food restaurant

Types of Systems

• Continuous Systems: whose inputs and outputs are capable of changing at any instant of time (e.g. car speed, electricity generator)
• Discrete Systems: one that changes state abruptly at discrete points in time (e.g. bank customers arriving)
• Deterministic Systems: previous status determines the new status (e.g. chemical experiment)
• Stochastic Systems: includes randomness during changing the status
• Closed Systems: a system that is completely isolated from its environment (internal effectiveness)
• Open Systems: one that accepts input from external sources and produces output (e.g. human body)

Advantages of Modeling and Simulations

• Safety: testing or experimenting without harming the person or environment
• Economic savings: designing and testing new products before prototypes or the final product is made
• Projection: looking into the future and highlighting potential impacts
• Visualization: seeing and understanding relationships
• Speed: speeding up or slowing down time
• Replication: looking at things under a variety of different scenarios

Disadvantages of Modeling and Simulations

• Mathematical calculations can be very complex
• Simulations may not identify real-life situations or activities
• Faulty or hidden assumptions
• Processing power and labor costs can be high
• Complexity and assumptions can lead to errors

Developing a Model

• Mathematical methods: probability theory, algebraic method, etc.
• Numerical computer-based simulation: simple and useful for complex systems

When to Use Simulation

• When studying internal interactions of a subsystem with complex system
• When simulating informational, organizational, and environmental changes
• When designing new systems or policies
• When training is needed
• When visualizing a plan with animated simulation

When Not to Use Simulation

• When the problem can be solved by common sense
• When the problem can be solved analytically
• When direct experiments are possible
• When costs exceed savings
• When resources or time are not available
• When system behavior is too complex