Sessions_13_14

Sessions_13_14 - models How to choose a queueing model All...

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models Page 1 How to choose a queueing model All models in this workbook are Poisson arrivals, infinite population, and FCFS. The models differ by (1) the service time distribution (exponential, constant or general) (2) the number of servers (single server or multiple servers) (3) waiting room capacity (unlimited waiting room or limited waiting room buffer) M/M/1 M/D/1 M/G/1 M/M/s Service time distribution Exponential Constant General Exponential Number of servers Single Single Single Multiple Waiting room capacity Unlimited Unlimited Unlimited Unlimited The Erlang Loss Model is a special case of M/M/s/b model where the waiting room capacity (b) is z The following models assume exponential distribution of service time: M/M/1, M/M/s, M/M/s/b The following models assume constant service time: M/C/1 The following models assume generally distributed (such as normal) service time: M/G/1 The following models assume a single server: M/M/1, M/C/1, M/G/1 The following models assume multiple servers: M/M/s, M/M/s/b The following models assume unlimited waiting room capacity: M/M/1, M/C/1, M/G/1, M/M/s The following models assume limited waiting room capacity: M/M/s/b
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models Page 2 M/M/s/b Exponential Multiple Limited zero.
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M-M-1 Page 3 Model 1 (M/M/1 Queue): Yellow cells need user inputed values Inputs Units of time hour Arrival rate (lambda) 16 cusomters per hour Service rate (mu) 20 cusomters per hour Outputs Direct outputs from inputs Mean time between arrivals 0.063 hour Mean time per service
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This note was uploaded on 05/08/2008 for the course BUAD 311 taught by Professor Vaitsos during the Spring '07 term at USC.

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Sessions_13_14 - models How to choose a queueing model All...

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