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MIT2_854F10_sim

# MIT2_854F10_sim - Introduction to Simulation Lecturer...

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Introduction to Simulation Lecturer: Stanley B. Gershwin

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What is Simulation? A computer simulation is a computer program ... that calculates a hard-to-calculate quantity using statistical techniques; OR that models the behavior of a system by imitating individual components of the system and their interactions. I am not entirely satisfied with this definition — it does not seem restrictive enough. If all goes well, you will know what a computer simulation is after this lecture.
What is Simulation? By contrast, a mathematical model is ... a mathematical representation of a phenomenon of interest. Computer programs are often used to obtain quantitative information about the thing that is modeled.

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What is Purposes Simulation? Simulation is used ... for calculating hard-to-calculate quantities ... from mathematics and science, from engineering, especially system design. for developing insight into how a system operates, for demonstrating something to bosses or clients.
What is Types of simulation Simulation? Static, for the evaluation of a quantity that is difficult to evaluate by other means. The evolution of a system over time is not the major issue. Dynamic, for the evaluation of quantities that arise from the evolution of a system over time.

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What is Types of simulation Simulation? Static — Monte Carlo Dynamic Discrete time Discrete event Solution of differential equations — I don’t consider this simulation, but others do.
Dynamic Discrete Time Simulation Simulation Appropriate for systems in which: Time is discrete. If time in the real system is continuous, it is discretized. There a set of events which have a finite number of possible outcomes. For each event, the outcome that occurs is independent of the other simultaneous events and of all past events. There is a system state which evolves according to the events that occur. That is, the system is a discrete time Markov chain. Often, other systems can be transformed into or approximated by discrete time Markov chains.

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Dynamic Discrete Time Simulation Simulation To model a random event that occurs with probability p , let u be a pseudo-random number which is distributed uniformly between 0 and 1.
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MIT2_854F10_sim - Introduction to Simulation Lecturer...

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