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Summary Simulation Modeling and Analysis

- Averill M Law
ISBN-13 9781259254383
387 Flashcards & Notes
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A snapshot of the summary - Simulation Modeling and Analysis Author: Averill M Law ISBN: 9781259254383

  • 1 Basic Simulation Modeling

  • 1.1 The Nature of Simulation

  • For what kinds of problems has simulation been found a useful and powerful tool?
    1. Designing and analyzing manufacturing systems.
    2. Analyzing supply chains.
    3. DeDesigning and operating transportation systems such as airports, freeways, ports and subways.
  • Objections against simulation:
    1. Models used to study large-scale systems tend to be very complex, and writing computer programs to execute them can be an arduous task indeed.
    2. A large amount of computer time is sometimes required.
    3. There appears to be an unfortunate impressions that simulation is just an exercise in computer programming, albeit a complicated one.
  • What's a system in the simulation

    the facility process of interest
  • 1.2 Systems, Models and Simulations

  • State of a system:
    collection of variables necessary to describe a system at a particular time, relative to the objectives of a study.
  • Ways to study a system:
    Look at figure.
  • 1.3 Discrete-Event Simulation

  • What are two principal approaches for advancing the simulation clock?
    1. Next-event time advance
    2. Fixed-increment time advance
  • If the main program invokes event routine i, what are the activities that occur?
    1. The system state is updated to account for the fact that an event of type i has occurred.
    2. Information about system performance is gathered by updating the statistical counters.
    3. The times of occurrence of future events are generated, and this information is added to the event list.
  • 1.3.1 Time-Advance Mevhanism

  • Why is it useful to write performance measures in integrals?
    Computationally, as the simulation progresses, the integrals can easily be accumulated by adding up areas of rectangles.
  • 1.4.1 Problem Statement

  • d(n): Expected Average delay in queue
    An average over a discrete number of observations --> discrete time statistic
  • Expected utilization proportion of the server
    server-busy function divided by T(n)
    = the expeteced proprotion of time during the simulation that the server is busy
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