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Simulation. Professor Stephen Lawrence Leeds School of Business University of Colorado Boulder, CO 80309-0419. Simulation Agenda. Types of simulation Uses of simulation Simulation examples Manual call center example Queueing simulation (spreadsheet) Financial simulation (spreadsheet)

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simulation

Simulation

Professor Stephen Lawrence

Leeds School of Business

University of Colorado

Boulder, CO 80309-0419

simulation agenda
Simulation Agenda
  • Types of simulation
  • Uses of simulation
  • Simulation examples
    • Manual call center example
    • Queueing simulation (spreadsheet)
    • Financial simulation (spreadsheet)
    • Commercial simulation products
  • Pros and cons of simulation
what is simulation
What is Simulation?
  • Process of creating mathematical models that represent real world business operations
    • Design and test new systems
    • Prevent unwise expenditures
    • Reduce risk
    • Maximize effectiveness of scarce resources
    • Anticipate problems, plan solutions

Systems Modeling Corp., CINEMA software demo, 1991

types of simulation
Types of Simulation
  • Continuous Time Simulation
    • Differential Equations (e.g., System Dynamics)
  • Discrete Event Simulation
    • Distinct events occur over time
    • Time of occurrence may be random
    • Examples
      • Job arrivals, machine breakdowns, patient emergencies, client calls, etc…
uses of simulation
Manufacturing

Auto parts

Apparel and textiles

Electronics

Food and beverages

Printing, newspapers

Metal fabrication

Consumer goods

Pharmaceuticals

Services

Airlines and airports

Distribution

Restaurants

Health care

Banking and finance

Transportation

Call/service centers

Defense

Uses of Simulation
types of problems examined
Types of Problems Examined
  • Scheduling resources, jobs, customers
  • Distribution and transportation
  • Allocation of employees
  • Materials handling
  • Communication networks
  • Facility layout
  • Ad infinitum…
manual call center simulation
Manual Call Center Simulation

New VentureCall Center is a contract call center for startup Internet businesses. Client customers call to place orders, ask questions, and receive questions. NVCC currently employs only a single operator. Call interarrival times are uniformly distributed on the interval [1,6] minutes. Service times are uniformly distributed on the interval [1,5] minutes. Unfortunately, the telephone switch used by NVCC is unreliable and frequently breaks down. Breakdowns occur at the end of a call with a probability of 1/12. Time to repair the breakdown is uniformly distributed on the interval [1,3] minutes.

manual call center simulation9

Job

Interarrival Time (rv)

Arrival Time

Start

Time

Processing Time (rv)

Finish

Time

Time in System

Time in Queue

Manual Call Center Simulation
queueing simulation
Queueing Simulation
  • General G/G/k queues
  • Collect standard performance queue performance statistics
  • Demonstrate queue variability
  • Excel Spreadsheet
financial simulation
Financial Simulation
  • Model future growth of several securities indices
  • Use historic performance to model future activity
  • Demonstrate market volatility
  • Excel spreadsheet
monte carlo simulation
Monte Carlo Simulation
  • Randomly sample variables
  • “Throw the dice” to determine variable values
  • Useful to determine range of outcomes
  • Commercial spreadsheet add-ins
    • Crystal Ball
    • @Risk
  • Excel example (Crystal Ball)
commercial simulation packages
Commercial Simulation Packages
  • Number of “easy to use” commercial simulation packages available
  • Prices range from $100’s to $10,000s
  • Examples
    • Simscript
    • ProSIM
    • MicroSaint
    • ARENA
    • Extend
issues with simulation
Issues with Simulation
  • Model Validation
    • Does model replicate current reality?
  • Experimental Design
    • Statistical design to “prove” results
  • Transient vs. Steady-State Behavior
pros and cons of simulation
Pros and Cons of Simulation
  • CONS
    • Difficult, time-consuming to build and maintain
    • Validation important but tricky
    • Does not optimize -- may settle for inferior results
  • PROS
    • Can model almost any complex business activity
    • Provides useful managerial insight
    • Allows extensive what-if analysis
    • Optimizing tools becoming available
simulation16

Simulation

Professor Stephen Lawrence

Leeds School of Business

University of Colorado

Boulder, CO 80309-0419