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Abstract
This thesis examines the multi-server bulk arrival systems with different service times and a bi-level breakdown. The consequences of breakdown on measures for system performance are examined using Monte Carlo techniques. A survey of queueing system simulation modeling of dynamic system is introduced. Routines and techniques for simulating random phenomena for both discrete and continuous behavior are included. A Monte Carlo study is performed to analyze a multi-server, bulk arrival (M[x]/M/C; C-1/FCFS) queueing system. The system breakdown limits the system to serve with either C or (C-1) servers. The server breakdown has equal chance over all servers in the system while the arrival process is a compound Poisson process and the distribution of the bulk size X is a positive Poisson bulk sizes. Measures of system performance including mean queue length, mean waiting time, and blocking probability are reported. Numerical results are obtained by simulation of the entire system. Computational analysis for (M[x]/EK/C; C-1/FCFS) heterogeneous queueing systems is discussed. Cases of relatively close values of the mean size of bulk to the number of servers are studied when heterogeneity of the servers is taken into account. Change in performance measures in response to traffic intensity and relative transition is shown.