account for large, bulk items$).$ Our usual assumption holds where the interarrival and service times follow an exponential distribution.

Iculate the average service rate $($in hours to match $).$

a$.9$ customers per hour

b$.72$ customers per hour

c$.16$ customers per hour

d$.12$ customers per hour

Clear my choice

since each server is expected to take on $\frac{}{s^{***}}$ arrivals. What is this optimal staffing level $s^{***}($number of servers$)?$

a$.25$ servers

b$.10$ servers

c$.20$ servers

d$.15$ senvers

For any one of the individual $s^{**}$ queues, what is the utilization of the server at the optimal staffing level $($optimal utilization$)?$

a$.0\mathrm{.}67$

b$.0\mathrm{.}8$

c$.0\mathrm{.}9$

d$.0\mathrm{.}75$

For any one of the individual $s^{**}$ queues, what is the probability distribution of the interarrival time, $A?$

a$.$ A Exponential$(6\mathrm{.}75)$

b$.$ A Exponential$(13\mathrm{.}5)$

c$.$ A Exponential$(9)$

d$.$ A Exponential$(5\mathrm{.}4)$

Considering any one of the individual $s^{***}$ queues, derive the expected number of customers waiting in line.

a$.0\mathrm{.}9$ customers

b$.3\mathrm{.}2$ customers

c$.2\mathrm{.}25$ customers

d$.8\mathrm{.}1$ customers

Considering any one of the individual $s^{**}$ queues, derive the expected waiting time $($seconds$)$ spent in line for a customer.

a$.1600$ seconds

b$.1200$ seconds

c$.900$ seconds

d$.1800$ seconds