8/22/01J. Hagstrom, U. of Illinois1 Simulation Jane Hagstrom

8/22/01J. Hagstrom, U. of Illinois2 Simulation Imitation of the behavior of a system, usually using a computer Examples: –Testing antibiotics against bacteria in a test tube –Flight simulation for pilots –Imitating behavior of customers, cashiers, and equipment in grocery checkout

8/22/01J. Hagstrom, U. of Illinois3 Why Do Simulation? Test system design before construction –Check for sympathetic vibration problems with a bridge Determine the effects of a change to an existing system –Decide whether to purchase another cash register station

8/22/01J. Hagstrom, U. of Illinois4 When Should We Do a Simulation? Consequences of bad design are expensive –bridge Expensive to experiment on existing system –Add new cash register station Disruptive or dangerous to experiment on existing system –Test antibiotic

8/22/01J. Hagstrom, U. of Illinois5 How Do We Do Simulation? Create a model that captures important and significant characteristics and behaviors of the real system Use the model to generate output data of interest concerning the system Analyze these output data

8/22/01J. Hagstrom, U. of Illinois6 Learning from Simulations Collecting data and creating the model aids in our understanding of the system Validation and verification of the model by system experts allows us to check our understanding of the system Statistical analysis gives scientific weight to our observations Statistical analysis is meaningless unless we have used good inputs

8/22/01J. Hagstrom, U. of Illinois7 Discrete-Event Simulation Imitates a dynamic system in which events occur at distinct moments in time Examples: –In a grocery checkout system, customers arrive, service starts and ends at distinct moments in time –In a telephone switching system, phone calls arrive and start and finish processing at distinct moments in time –In a freight-forwarding system, freight arrives, is assembled into a truckload, and is loaded onto a truck at distinct moments in time

8/22/01J. Hagstrom, U. of Illinois8 Stochastic Simulation A simulation which captures chance happenings in the system Examples: –In a grocery checkout system, the number of items in a grocery cart is random –The time at which a phone call arrives at a switching station is random –The time required to verify loan application information is random