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The flow in a downtown restaurant is measured in parties, where
a party is a group of people that will use a single table. The
restaurant has ten tables and waiting space for five parties.
On a rainy evening, the arrival rate to the restaurant is 10
parties per hour. Once seated, the average time for a party
to complete the ordering and eating process is one hour. The
time between arrivals has an exponential distribution. Although
the service process is not exponential we make the Poisson assumption
for analysis purposes. When an arriving party finds the waiting
spaces full, it does not stay. Rather it rushes off to a neighboring
fast food restaurant that has no limit to service. Part of the
analysis for this system appears below. Fill in the empty cells.
Times are in hours.
Quantity
|
Value
|
Units |
Type
|
|
|
Mean Number in Queue
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1.55
|
parties |
Mean Time in Queue
|
|
hours |
Mean Number in Service
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|
parts |
Mean Time in Service
|
1
|
hour |
Throughput Rate
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|
parts/hour |
Prob. all servers are busy
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0.621
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Prob. System Full
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0.104
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If the restaurant adds another waiting space (to make 6 in
all), how will the Prob. All Servers Busy change?
(up, down, or stay the same) Justify your conclusion.
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