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Introduction to Simulation Modeling

Introduction to Simulation Modeling. Jason R. W. Merrick. Systems. System – facility or process, actual or planned Examples abound …. Manufacturing facility Bank or other personal-service operation Transportation/logistics/distribution operation

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Introduction to Simulation Modeling

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  1. Introduction to Simulation Modeling Jason R. W. Merrick

  2. Systems • System – facility or process, actual or planned • Examples abound … • Manufacturing facility • Bank or other personal-service operation • Transportation/logistics/distribution operation • Hospital facilities (emergency room, operating room, admissions) • Computer network • Freeway system • Business process (insurance office) • Criminal justice system • Chemical plant • Fast-food restaurant • Supermarket • Theme park • Emergency-response system Chapter 1 Introduction to Simulation Modeling

  3. Work With the System? • Study the system – measure, improve, design, control • Maybe just play with the actual system • Advantage — unquestionably looking at the right thing • But it’s often impossible to do so in reality with the actual system • System doesn’t exist • Would be disruptive, expensive, or dangerous Chapter 1 Introduction to Simulation Modeling

  4. Models • Model – set of assumptions/approximations about how the system works • Study the model instead of the real system … usually much easier, faster, cheaper, safer • Can try wide-ranging ideas with the model • Make your mistakes on the computer where they don’t count, rather than for real where they do count • Often, just building the model is instructive – regardless of results • Model validity (any kind of model … not just simulation) • Care in building to mimic reality faithfully • Level of detail • Get same conclusions from the model as you would from system • More in Chapter 12 Chapter 1 Introduction to Simulation Modeling

  5. Computer Simulation • Broadly interpreted, computer simulation refers to methods for studying a wide variety of models of systems • Numerically evaluate on a computer • Use software to imitate the system’s operations and characteristics, often over time • Can be used to study simple models but should not use it if an analytical solution is available • Real power of simulation is in studying complex models • Simulation can tolerate complex models since we don’t even aspire to an analytical solution Chapter 1 Introduction to Simulation Modeling

  6. Advantages of Simulation • Flexibility to model things as they are (even if messy and complicated) • Avoid looking where the light is (a morality play): • You’re walking along in the dark and see someone on hands and knees searching the ground under a street light. • You: “What’s wrong? Can I help you?” • Mr. X: “I dropped my car keys and can’t find them.” • You: “Oh, so you dropped them around here, huh?” • Mr. X : “No, I dropped them over there.” (Points into the darkness.) • You: “Then why are you looking here?” • Mr. X : “Because this is where the light is.” • Allows uncertainty, nonstationarity in modeling • The only thing that’s for sure: nothing is for sure • Danger of ignoring system variability • Model validity Chapter 1 Introduction to Simulation Modeling

  7. System vs. Its Model • Simplification • Abstraction • Assumptions Model Real System Understanding Chapter 1 Introduction to Simulation Modeling

  8. Physical (prototypes) Analytical (mathematical) Computer (Monte Carlo Simulation) Descriptive (performance analysis) Prescriptive (optimization) Model Classification Chapter 1 Introduction to Simulation Modeling

  9. Physical (Prototypes) Chapter 1 Introduction to Simulation Modeling

  10. Analytical (Mathematical) Single Stage Queuing Model Chapter 1 Introduction to Simulation Modeling

  11. Computer (Monte Carlo Simulation) Chapter 1 Introduction to Simulation Modeling

  12. Descriptive (Performance analysis) Simulation vs. Real World Chapter 1 Introduction to Simulation Modeling

  13. Prescriptive (Optimization) Chapter 1 Introduction to Simulation Modeling

  14. Typical Uses of Simulation • Estimating a set of productivity measures in production systems, inventory systems, manufacturing processes, materials handling and logistics operations. • Designing and planning the capacity of computer systems and communication networks so as to minimize response times. • Conducting war games to train military personnel or to evaluate the efficacy of proposed military operations • Evaluating and improving maritime port operations, such as container ports or bulk-material marine terminals (coal, oil or minerals), so as to find ways of reducing vessel port times. • Improving health care operations, financial and banking operations, transportation systems and airports, among many others. Chapter 1 Introduction to Simulation Modeling

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