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Unit 1 introduction to simulation
- 1. Unit 1-Introduction tosimulation
- 2. Definition • A simulationis the imitation of the operation of real-world process or system over time. • … Generation of artificial history and observation of that observation history • „A model construct a conceptual framework that describes a system. • „The behavior of a system that evolves over time is studied by developing a simulation model. • „The model takes a set of expressed assumptions: … Mathematical, logical … Symbolic relationship between the entities
- 3. Goal of modelingand simulation • A model can be used to investigate a wide verity of “what if” questions about real-world system. … Potential changes to the system can be simulated and predicate their impact on the system. … Find adequate parameters before implementation • „So simulation can be used as … Analysis tool for predicating the effect of changes … Design tool to predicate the performance of new system • „It is better to do simulation before Implementation.
- 4. How a modelcan be developed? • Mathematical Methods … Probability theory, algebraic method ,… … Their results are accurate … They have a few Number of parameters … It is impossible for complex systems • „Numerical computer-based simulation … It is simple … It is useful for complex system
- 5. When Simulation Isthe Appropriate Tool • Simulation enable the study of internal interaction of a subsystem with complex system • „Informational, organizational and environmental changes can be simulated and find their effects • „A simulation model help us to gain knowledge about improvement of system • „Finding important input parameters with changing simulation inputs • „Simulation can be used with new design and policies before implementation • „Simulating different capabilities for a machine can help determine the requirement • „Simulation models designed for training make learning possible without the cost disruption • „A plan can be visualized with animated simulation • „The modern system (factory, wafer fabrication plant, service organization) is too complex that its internal interaction can be treated only by simulation
- 6. When Simulation IsNot Appropriate • When the problem can be solved by common sense. • „When the problem can be solved analytically. • „If it is easier to perform direct experiments. • „If cost exceed savings. • „If resource or time are not available. • „If system behavior is too complex. … Like human behavior
- 7. Advantages and disadvantagesof simulation • „In contrast to optimization models, simulation models are “run” rather than solved. … Given as a set of inputs and model characteristics the model is run and the simulated behavior is observed
- 8. Advantages of simulation •New policies, operating procedures, information flows and soon can be explored without disrupting ongoing operation of the real system. • New hardware designs, physical layouts, transportation systems and … can be tested without committing resources for their acquisition. • Time can be compressed or expanded to allow for a speed-up or slow-down of the phenomenon( clock is self-control). • Insight can be obtained about interaction of variables and important variables to the performance. • Bottleneck analysis can be performed to discover where work in process, the system is delayed. • A simulation study can help in understanding how the system operates. • “What if” questions can be answered.
- 9. Disadvantages of simulation •Model building requires special training. … Vendors of simulation software have been actively developing packages that contain models that only need input (templates). • Simulation results can be difficult to interpret. • Simulation modeling and analysis can be time consuming and expensive. … Many simulation software have output- analysis.
- 10. Areas of application •Manufacturing Applications • Construction Engineering and project management • Military application • Logistics, Supply chain and distribution application • Transportation modes and Traffic • Business Process Simulation • Risk analysis … Insurance, portfolio,...
- 11. Application of Simulationin Business • Process Improvement • Predicting Outcomes • Managing Risk • Deciding on Actions • Improving Forecasts • Exploring Possible Scenarios
- 12. Business simulation (game) •Used for business training, education or analysis. • It includes strategic thinking, decision making, problem solving, financial analysis, market analysis, and operations. • It can be scenario-based or numeric-based. Significance Risk-free decision making A way to mimic on-the-job learning Realism
- 13. Example of decisionmaking
- 14. Discrete and ContinuesSystems • A discrete system is one in which the state variables change only at a discrete set of points in time : Eg Bank
- 15. Discrete and ContinuesSystems (cont.) • A continues system is one in which the state variables change continuously over time: Head of water behind the dam
- 16. Model of aSystem • To study the system … it is sometimes possible to experiments with system … This is not always possible (bank, factory,…) … A new system may not yet exist • Model: construct a conceptual framework that describes a system … It is necessary to consider those accepts of systems that affect the problem under investigation (unnecessary details must remove)
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- 18. Characterizing a SimulationModel • Deterministic or Stochastic • In deterministic models, the output of the model is fully determined by the parameter values and the initial conditions initial conditions. • Stochastic models possess some inherent randomness. The same set of parameter values and initial conditions will lead to an ensemble of different outputs. … Does the model contain stochastic components? … Randomness is easy to add to a DES • Static or Dynamic … Is time a significant variable? • Continuous or Discrete … Does the system state evolve continuously or only at discrete points in time? … Continuous: classical mechanics … Discrete: queuing, inventory, machine shop models
- 19. Discrete-Event Simulation Model •Stochastic: some state variables are random • Dynamic: time evolution is important • Discrete-Event: significant changes occur at discrete time instances,state variables change with time.
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- 21. Verification vs. Validation •Verification … Computational model should be consistent with specification model … Did we build the model right? • Validation … Computational model should be consistent with the system being analyzed … Did we build the right model? … Can an expert distinguish simulation output from system output?
- 23. • Problem formulation:Problem is understood by simulation analyst and formulation is understood by client. • Setting the objective and project plan: Determine the questions that are to be answered Identify scenarios to be investigated Decision criteria Determine the end user Determine data requirement Determine hardware, software Prepare a time plan Cost plan and billing procedure • Conceptual model: Abstract essential features-events,activities,entities,attribtes,resources,variables and their relationships Performance measure Data requirements • Assumptions-clearly to be specified
- 24. • Experimental design Number of simulation runs Length of each run Manner of initialization • Analysis of results Statistical test(point estimation) Interpretation of results More runs? • Documentation and reporting • Progress report • Frequent report • Result of experiments • Recommendations.
- 25. Various simulation Techniques •Monte Carlo / Risk Analysis Simulation Businesses use it prior to implementing a major project or change in a process, such as a manufacturing assembly line. • Agent-Based Modeling & Simulation An agent-based simulation is a model that examines the impact of an ‘agent’ on the ‘system’ or ‘environment.’ • Discrete Event Simulation A discrete event simulation model enables you to observe the specific events that result in your business processes. • System Dynamics Simulation Solutions This is a very abstract form of simulation modeling, system dynamics does not include specific details about the system