OPER1021 Lecture Notes - Lecture 4: Discrete Event Simulation, Flowchart
25 Jan 2017
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Document Summary
Simulation is a very broad term methods and applications to imitate or mimic real systems, usually via computer. Simulation can be used to measure, improve, design, or control (stabilize) processes. Alternative: play with the actual process: advantage. Unquestionably looking at the right thing: disadvantages. Continuous change v. discrete change: can state change continuously, or only at discrete points in time. Deterministic v. stochastic: is everything for sure or is there uncertainty. Most operational models: dynamic, discrete change, stochastic. Monte carlo simulation estimating possible outcomes by substitution a range of values (i. e. a probability distribution) for any factor that has inherent uncertainty: static. Discrete event simulation models the operation of a system as sequence of discrete events in time: dynamic. Airport operations (passengers, security, planes, crews, baggage) Hospital facilities (emergency room, operating room, admissions) Ability to study complex systems: flexibility to model things as they are (even if messy and complicated) Allows for uncertainty and nonstationarity in modeling.
