<<1234567891011121314151617181920212223242526272829303132333435363738394041424344454647>> 1. What is the primary purpose of simulation?To create new systemsTo study effects of changes in the real system through modelsTo replace real-life conditionsTo avoid the use of mathematical modelsQuestion 1 of 47 2. How is simulation defined in the context of studying systems?Imitating only positive outcomesImitating random occurrencesImitating actual or probable real-life conditions, events, or situationsImitating imaginary scenariosQuestion 2 of 47 3. What is the goal of simulation in relation to predicting actual behavior?To create uncertaintyTo replace actual systemsTo imitate a system or environment for predictionTo simplify realityQuestion 3 of 47 4. How is simulation described in terms of imitating real-life conditions or events?A mathematical equationA random occurrenceAn imitation of actual or probable real-life conditionsA fictional scenarioQuestion 4 of 47 5. What can a simulation be performed through?Solving a set of equations onlyConstructing a physical model onlyStage rehearsal onlySolving a set of equations, constructing a physical model, stage rehearsal, computer graphics, or gameQuestion 5 of 47 6. What is one form of a mathematical model used in simulation?Physical modelsStage rehearsalComputer graphicsSolving a set of equationsQuestion 6 of 47 7. Why are simulations considered useful tools?To increase risk exposureTo simplify realityTo allow experiments without actual exposure or riskTo eliminate underlying assumptionsQuestion 7 of 47 8. What is emphasized about simulations in terms of reality?They replace realityThey are accurate representations of realityThey may be gross simplifications of realityThey eliminate all assumptionsQuestion 8 of 47 9. What determines the effectiveness of simulations?Random occurrencesUnderlying assumptionsComplexity of realityComputer graphicsQuestion 9 of 47 10. How are simulations described in terms of their accuracy?They perfectly mimic realityThey replace realityThey are as good as underlying assumptionsThey eliminate all uncertaintiesQuestion 10 of 47 11. How is simulation extensively used in driving lessons?By providing theoretical lessons onlyBy avoiding real road situationsBy imitating real road situations during learningBy eliminating all risksQuestion 11 of 47 12. What is one example of the application of simulation in the financial world?Cooking classesDriving lessonsStock marketWeather forecastingQuestion 12 of 47 13. In which areas of the financial world is simulation commonly used?Cooking and bakingForex, investment, and risk managementTravel and tourismFashion and designQuestion 13 of 47 14. What is an example of the application of simulation methods in transportation?Cooking and bakingRailroad operationsFacility layoutAir Traffic control queuingQuestion 14 of 47 15. What is a specific use of simulation in manufacturing?Cooking and bakingAir Traffic control queuingAssembly line schedulingForeign exchange marketQuestion 15 of 47 16. Which area involves the application of risk modeling using simulation methods?Fashion and designCooking and bakingRisk modeling in financeTravel and tourismQuestion 16 of 47 17. What does simulation help avoid in the context of driving lessons?Theoretical lessonsReal road situationsSerious accidentsComplexity in learningQuestion 17 of 47 18. Which area is NOT mentioned as an application of simulation methods?Facility layoutWeather forecastingStock marketAircraft maintenance schedulingQuestion 18 of 47 19. What is the primary reason for using simulation in situations with size and/or complexity?To simplify the problemTo eliminate risksTo make the use of other techniques easyTo overcome the difficulty or impossibility of using other techniquesQuestion 19 of 47 20. What do simulation models replicate?Fictional scenariosImaginary systemsReal systemsTheoretical conceptsQuestion 20 of 47 21. What are the three types of processes used in representative simulation models?Chemical, physical, and biologicalArithmetic, analog, and logicalMechanical, electrical, and thermalDigital, manual, and automatedQuestion 21 of 47 22. What do executable processes in simulation models predict?Static propertiesRandom occurrencesDynamic properties of the actual systemFixed outcomesQuestion 22 of 47 23. What is the role of time incrementation in simulation models?To eliminate probabilitiesTo predict the pastTo handle irregular eventsTo replace simulated clocksQuestion 23 of 47 24. What are the two methods of time incrementation in simulation models?Daily and nightly incrementsRegular and irregular incrementsFixed and variable incrementsPredictable and unpredictable incrementsQuestion 24 of 47 25. What type of events do fixed time increments in simulation models suit?Irregular eventsDaily occurrencesInfrequent eventsVariable eventsQuestion 25 of 47 26. Which events are handled by variable time increments in simulation models?Regular eventsPredictable eventsIrregular, infrequent eventsFixed eventsQuestion 26 of 47 27. What can variable increments incorporate in simulation models?Fixed probabilitiesPredictable outcomesProbabilities for time incrementsDaily incrementsQuestion 27 of 47 28. What type of systems do simulation models excel in handling compared to other models?Static systemsPredictable systemsDynamic systemsFixed systemsQuestion 28 of 47 29. In summary, what do simulation models replicate using processes that predict dynamic properties?Imaginary scenariosStatic propertiesReal systemsTheoretical conceptsQuestion 29 of 47 30. How are simulation models customized?They are generic and cannot be customizedThey are adapted across various situationsThey are tailored to specific problemsThey are rigid and unchangeableQuestion 30 of 47 31. What is the contrast between simulation models and linear programming models in terms of adaptability?Simulation models are adaptable across various situations, while linear programming models lack specificity.Linear programming models are adaptable across various situations, while simulation models lack specificity.Both simulation and linear programming models lack adaptability.Both simulation and linear programming models are highly specifiC)Question 31 of 47 32. What is inherent in the design and application of building and executing simulation models?Rigidity and strict rulesAdaptability and flexibilityGeneric applicationSpecificity and lack of variationQuestion 32 of 47 33. How are building and executing models considered in the context of guidelines?Strict rulesGeneral principlesGeneric methodsGuidelines, not strict rulesQuestion 33 of 47 34. What is a crucial aspect of run length strategies in simulations?Fixed periodLarge sample sizeEquilibrium attainmentAll of the aboveQuestion 34 of 47 35. Which type of run length strategy matches simulated data to historical data for accuracy in scenarios like demand simulations?Fixed periodLarge sample sizeEquilibrium-oriented runsNone of the aboveQuestion 35 of 47 36. What is the role of equilibrium-oriented runs in simulations?To introduce randomnessTo match simulated data to historical data for accuracyTo eliminate historical dataTo reduce the sample sizeQuestion 36 of 47 37. What does the discrimination of run length in simulations involve?Ignoring historical dataConsidering only large sample sizesChoosing between fixed period, large sample size, and equilibrium attainment strategiesIgnoring the specificity of simulation modelsQuestion 37 of 47 38. What does the customization of simulation models allow for?Generic applicationAdaptability across various situationsSpecific tailoring to unique problemsStrict adherence to rulesQuestion 38 of 47 39. What is the primary difference in adaptability between simulation models and linear programming models?Linear programming models are adaptable across various situations, while simulation models lack specificity.Simulation models are adaptable across various situations, while linear programming models lack specificity.Both simulation and linear programming models lack adaptability.Both simulation and linear programming models are highly specifiC)Question 39 of 47 40. Under what circumstances is simulation desirable instead of conducting experiments on the real system?When experiments are cheap and easily manageableWhen experiments would disrupt ongoing activitiesWhen experiments are short in durationWhen experiments are exact replications of eventsQuestion 40 of 47 41. Why is simulation preferred in situations where experiments on the real system would be too costly?Because simulation is always cheaperBecause simulation is the only optionBecause it reduces costs compared to real experimentsBecause it is equally costly as real experimentsQuestion 41 of 47 42. In what scenarios does simulation become advantageous due to the requirement for many observations over an extended period of time?When observations are short-term and immediateWhen observations are sporadicWhen observations require an extended period of timeWhen observations are exact replicationsQuestion 42 of 47 43. Why is simulation preferable when exact replication of events is not possible in real experiments?Because simulation always ensures exact replicationBecause exact replication is not necessary in simulationBecause real experiments always allow exact replicationBecause exact replication is possible in all experimentsQuestion 43 of 47 44. When is simulation considered advantageous due to the lack of control over key variables in real experiments?When key variables are easy to controlWhen exact control is not requiredWhen key variables can be manipulated easilyWhen control over key variables is not possibleQuestion 44 of 47 45. Under what conditions is simulation preferable when a mathematical model is not available to handle the problem?When mathematical models are readily availableWhen mathematical models are too complexWhen mathematical models are simpleWhen mathematical models are robustQuestion 45 of 47 46. Why might simulation be chosen when a problem's complexity surpasses the capability of available personnel?Because available personnel are always capableBecause simulation is not effective in handling complex problemsBecause simulation can handle complex problems beyond personnel capabilityBecause personnel can easily handle any level of complexityQuestion 46 of 47 47. When is simulation advantageous over a mathematical model that is not robust enough to provide information on all factors of interest?When mathematical models are always robustWhen robustness is not a factor in decision-makingWhen a mathematical model is not robust enough to cover all factors of interestWhen factors of interest are not important in decision-makingQuestion 47 of 47 Loading...
