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MODES-650 Advanced System Simulation

MODES-650 Advanced System Simulation. REPRESENTING AND GENERATING UNCERTAINTY EFFECTIVELY. W. David Kelton. Presented by Olgun Karademirci http://www.karademirci.net. 5.11. 20 10. 4. W. DAVID KELTON. Professor Director , Master of Science in Quantitative Analysis (MSQA) Program

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MODES-650 Advanced System Simulation

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  1. MODES-650 AdvancedSystemSimulation REPRESENTING AND GENERATING UNCERTAINTY EFFECTIVELY W. David Kelton Presented by Olgun Karademirci http://www.karademirci.net 5.11.2010

  2. 4 W. DAVID KELTON ProfessorDirector, Master of Science in Quantitative Analysis (MSQA) Program Department of Quantitative Analysis and Operations Management University of Cincinnati Cincinnati, Ohio His Interests • Computer simulation methods and applications • Applied stochastic processes • Operations research • Statistical methods

  3. OUTLINE

  4. Scope and purpose • Suggestions for new ways of generating random inputs in simulation-modeling software is the scope of this study. • Purpose of the author in writing this proceeding is to discuss approaches for effective generation of uncertain inputs in computer-simulation models.

  5. Different kinds of simulation models and inputs • Deterministic Simulations – Stochastic Simulations • Static Simulation Model – Dynamic Simulation Model • Structural Components – Quantitative Components • Deterministic Inputs – Random Inputs

  6. Common assumption about random inputs • Mutually independent random inputs • Random inputs itself as a stream of independent and identically distrubution

  7. Common assumption about random inputs • Example-1; A patient arriving to an urgent-care facility • Example-2; A telecommunications system • Example-2; A call center

  8. Generating and representing random input to a simulation • Using actual data (observed) • Fitting data • Empirical distribution

  9. Assigning random numbers to improve precision • Random number generation • Pseudo • True

  10. Conclusions • Importance of input random process • Model’s Validity – Model Precision

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