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Simulation Some problems queueing system can not be solved by analytical methods. Between Other reasons could be cited the existence of non-standard input patterns and service, a modeling system complexity or the nature of the queue discipline. Moreover, sometimes, the analytical results are for a state stationary that never reached, because the system is interrupted before leave the transient state. In these cases the analysis by simulation queues can be a good technique to find the result. Of note, in any queueing system software case, if there are analytical models, these They should be used.
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Although the simulation can solve or approximate the resolution of many intractable problems is not the panacea to solve given by simulation it is comparable to perform an experiment. Therefore, there to use all the tools associated with the design and analysis of experiments: Collection and Data Analysis, conducting experiments, analysis and consistency of results, etc.Another defect of the use of simulation versus analytical methods, It occurs when the objective is to design a system and no evaluation. In that If simulation analysis does not allow use optimization techniques conventional, although admittedly some simulation tools incorporate stochastic optimization techniques to solve this type of problems. Elements of a Simulation Model.
Theory of tails Page of Given that we are interested in modeling systems stochastic data entry should represent the most reliable way possible reality. Sometimes use data from the same to recognize the structure of the data entry. The simulation run is currently done through packages advanced computer (called VIMS). The analysis of results has to do with the calculation of the effectiveness of the system using techniques appropriate statistics. Further, model validation is a requirement that often overlooked when making models, q is to check that the system reacts as it does reality.
Modeling Entries Modeling queueing systems of the inputs is a requirement not only of the simulation, but any kind of numerical analysis and probabilistic. The two biggest problems in the modeling of the input data are family selection of statistical distributions and once beloved family estimating the parameters that define the function of the different entries. The first of the two problems is obviously view more complicated as the second is approachable only once resolved the family selection statistical distributions. In many cases simulation packages often carry a tool Statistical adjustment. When this does not happen we will have to resort to different statistical techniques to define both families parameters.
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Analysis of Results Reach valid conclusions from the results requires a large and careful effort. When simulate stochastic systems, not possible drawing conclusions from a single simulation is by nature statistics. So to draw conclusions necessary to design and queueing system software implement experiments in a way logical and comprehensive. There are two types of simulation: continuous or interrupted. A Model simulation interrupted as a bank that opens at: and closes at Queuing Theory Page of: emptying the tail end of the service. There are four elements to consider when addressing a simulation model of queuing theory, it designed the course "physical" model: a) Selection of input data b) Simulation. c) Analysis of results d) Validation of the model.
However, a continuum model could be associated with a production system where the job that is just one day, is the one that begins the next day. If the latter is when interest results in the steady state. In systems that lead to models interrupted the steady state is generally irrelevant. What matters is the average value of collecting calculable A number of results, always admitting that what you get is an average value estimated at a confidence interval. In systems that lead to continuous models the problem is a little more complicated, because you have to remove the samples the transient state, but the definition of transient state require state recognition and stable both the transient state.