Simulation modeling and analysis
This authoritative, comprehensive, and thoroughly up-to-date guide addresses all the important aspects of a simulation study, including modeling, simulation languages, validation, input probability distribution, and analysis of simulation output data. Full scale treatments of manufacturing systems simulation and simulation software and animation are also included along with useful and instructive case studies.
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Basic Simulation Modeling
FixedIncrement Time Advance
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acceptance-rejection method algorithm alias method approach average delay batch Chap confidence interval configurations correlation covariance-stationary define delay in queue density function discrete discussed in Sec distribution function estimate event list event type example exponential distribution exponential random factors FIFO FIGURE forklift FORTRAN fprintf(outfile gamma gamma distribution given histogram idle independent initial integer interarrival inverse-transform method job type machine manufacturing system mean metamodel Note number in queue number of customers observations obtain output data percent confidence interval plot Poisson process Prob probability procedure Q-Q plot queueing model queueing system random numbers random variables replications sample sampst scale parameter scheduled server sim_time simlib simulation simulation model simulation packages simulation run simulation study single-server queueing specified station statistical steady-state stochastic stochastic process Suppose Table teller throughput tion update valid variance variates vector Weibull Weibull distribution