The SIMSCRIPT provides a process-based approach of writing a simulation program. Events exist autonomously and they are discrete so between the execution of two events nothing happens. The points in time that an event is activated are randomized, so no input from outside the system is required. The activities of the model consist of events, which are activated at certain points in time and in this way affect the overall state of the system. As this approach is more reliable, the simulation approach gives more flexibility and convenience. The simulation approach of analyzing a model is opposed to the analytical approach, where the method of analyzing the system is purely theoretical.
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Instead of building extensive mathematical models by experts, the readily available simulation software has made it possible to model and analyze the operation of a real system by non-experts, who are managers but not programmers.Ī simulation is the execution of a model, represented by a computer program that gives information about the system being investigated. System Simulation is the mimicking of the operation of a real system, such as the day-to-day operation of a bank, or the value of a stock portfolio over a time period, or the running of an assembly line in a factory, or the staff assignment of a hospital or a security company, in a computer. The availability of effective visual modeling and simulation enables the analyst and the decision-maker to boost their dynamic decision by rehearsing strategy to avoid hidden pitfalls. This skill lies at the heart of successful strategic decision process. Analogous to the holodeck in the popular science-fiction television program Star Trek, simulations generate dynamic environments with which users can interact "as if they were really there." Such simulations are used extensively today to train military personnel for battlefield situations, at a fraction of the cost of running exercises involving real tanks, aircraft, etc.ĭynamic modeling in organizations is the collective ability to understand the implications of change over time. Another important application of simulation is in developing "virtual environments", e.g., for training. Simulation early in the design cycle is important because the cost to repair mistakes increases dramatically the later in the product life cycle that the error is detected. Most if not all digital integrated circuits manufactured today are first extensively simulated before they are manufactured to identify and correct design errors. In addition to its use as a tool to better understand and optimize performance and/or reliability of systems, simulation is also extensively used to verify the correctness of designs. The scenario described above is but one situation where computer simulation can be effectively used. We need a proper knowledge of both the techniques of simulation modeling and the simulated systems themselves. In this Web site we study computer systems modeling and simulation. Modeling and simulation of system design trade off is good preparation for design and engineering decisions in real world jobs. Introduction & Summary Computer system users, administrators, and designers usually have a goal of highest performance at lowest cost. "What-if" Analysis Techniques IntroductionĮxponential Tangential in Expectation Method Metamodeling and the Goal seeking Problems Introduction Simulation-based Optimization Techniques Introduction Techniques for Sensitivity Estimation Introduction System Dynamics and Discrete Event Simulation Determination of Simulation Runs Simulation Software Selection.Techniques for the Steady State Simulationĭetermination of the Desirable Number of Simulation Runs Simulation Output Data and Stochastic Processes Topics in Descriptive Simulation Modeling Modeling & Simulation Goodness-of-Fit for Poisson Uniform Density Function.Statistics and Probability for Simulation
Metamodeling and the Goal seeking Problems.