3 Introduction Definition Brief History Applications “Real World” ApplicationsThe advantage of simulationThe disadvantages of simulation
4 Definition: “Simulation is the process of designing a model of a real system and conductingexperiments with this model for thepurpose of either understanding thebehavior of the system and/orevaluating various strategies for theoperation of the system.”- Introduction to Simulation Using SIMAN(2nd Edition)
5 Systemdefinition: System is a collection of entities (people, parts, messages, machines, servers, …) that act and interact together toward some end (Schmidt and Taylor, 1970)In practice, depends on objectives of studyMight limit the boundaries (physical and logical) of the systemJudgment call: level of detail (e.g., what is an entity?)Usually assume a time element – dynamic systemState of a system: Collection of variables and their values necessary to describe the system at that timeMight depend on desired objectives, output performance measuresBank model: Could include number of busy tellers, time of arrival of each customer, etc.
8 Types of systems Discrete Continuous State variables change instantaneously at separated points in timeBank model: State changes occur only when a customer arrives or departsContinuousState variables change continuously as a function of timeHead of water behind the dam : State variables Head amount change continuouslyMany systems are partly discrete, partly continuous
9 Ways to study a system Simulation is “method of last resort?” Maybe … But with simulation there’s no need (or less need) to “look where the light is”
10 Modeling construct a conceptual framework that describes a system Modeling is a way of looking at the worlda system can have multiple contradictory modelsWe need to use models because resources are limitedModels simplified thingUsing the appropriate model allows us to make decisions, even when the situation is complex or resources are limitedWe are always using models
11 Simulating“Simulation is the process of designing a model of a real system and conducting experiments with this model for the purpose of either understanding the behavior of the system and/or evaluating various strategies for the operation of the system.”To simulate any system we need at first to build a model for that system then simulate this modelTypes of simulation models:Physical simulation modelsMathematical simulation modelsStatic vs. dynamicDeterministic vs. stochasticContinuous vs. discrete(Most operational models are dynamic, stochastic, and discrete – will be called discrete-event simulation models)
13 Simulation allows us to: Why we need simulation ?Because the real system is:too cumbersome (ثقيل)too costlytoo dangeroustoo slowSimulation allows us to:Model complex systems in a detailed wayDescribe the behavior of systemsConstruct theories or hypotheses that account for the observed behaviorUse the model to predict future behavior, that is, the effects that will be produced by changes in the systemAnalyze proposed systems
14 Help-desk operator example Help- desk operator has two statesBusy helping someonewaiting for a call to come in.Events:Customer starts describing problem to help deskCustomer completes telephone conversationSimulation starts at t= t0 = 0First customer arrives at t1, simulation time is now t= t0 + t1Help desk requires ts to resolve issueFirst customer leaves at t= t0 + t1 + tsSecond customer arrives at t2If t2< t0 + t1 + ts then customer must waitIf t2> t0 + t1 + ts then customer starts services
15 Brief History Not a very old technique... World War II“Monte Carlo” simulation: originated withthe work on the atomic bomb. Used tosimulate bombing raids. Given thesecurity code name “Monte-Carlo”.Still widely used today for certain problemswhich are not analytically solvable (forexample: complex multiple integrals…)
16 Brief History (cont.) Late ‘50s, early ‘60s Computers improve First languages introduced: SIMSCRIPT, GPSS (IBM)Simulation viewed at the tool of “last resort”Late ‘60s, early ‘70sPrimary computers were mainframes: accessibilityand interaction was limitedGASP IV introduced by Pritsker. Triggered a waveof diverse applications. Significant in the evolutionof simulation.
17 Brief History (cont.) Late ‘70s, early ‘80s SLAM introduced in 1979 by Pritsker and Pegden.Models more credible because of sophisticated tools.SIMAN introduced in 1982 by Pegden. First languageto run on both a mainframe as well as amicrocomputer.Late ‘80s through presentPowerful PCsLanguages are very sophisticated (market almostsaturated)Major advancement: graphics. Models can now beanimated!
18 What can be simulated? Almost anything can and almost everything has...
20 Advantages of Simulation Can be used to study existing systems without disrupting the ongoing operations.Proposed systems can be “tested” before committing resourcesCan handle large and complex systemsCan answer “what-if” questionsDoes not interfere with the real systemAllows study of interaction among variables“Time compression” is possibleHandles complications that other methods can’t
21 Disadvantages of Simulation Can be expensive and time consumingManagers must choose solutions they want to try (“what-if” scenarios)Each model is uniqueModel building is an art as well as a science. The quality of the analysis depends on the quality of the model and the skill of the modeler (Remember: GIGO)Simulation results are sometimes hard to interpret.Should not be used when an analytical method would provide for quicker results.