## Robustness of Queueing Models |

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arrival data arrival process arrivals and service assumption average idle average number Axiom binomial probability calculate constant mean arrival cost curve cost model cost ratio Cw/Cs decimal random number dividing the shift E(TVC experimental conditions F-Test flow diagram follows homogeneous Poisson process Homogeneous Poisson Test increased intensity function mean arrival rate mean value function mean waiting method nonhomogeneous Poisson process null hypothesis number of arrivals number of servers number of units optimum number optimum solution Parzan probability distribution Probability of type procedure queueing model queueing system Queueing Theory random variables robustness sample sample size SERATE service facility shift period shown in fig significance level significant at 0.10 simulation model Simulation Program single server starting values statistical tests statistically independent test the arrivals test the hypothesis Total variable cost TVC/Cs TVC1 TVC2 TVC3 type I error variance