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Exam 20: Queuing Analysis

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Question 1

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With a restaurant as an example, discuss the psychological methods used to affect customers' perceptions of waiting to be seated, to be served, etc.).

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Even though actual wait time may be 40 m...

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Question 2

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A small software company hired a Customer Service Representative CSR) to handle technical support questions. It is estimated that during peak periods, the CSR would receive four 4) calls per hour and follow a Poisson distribution. Based on past experience, a CSR can handle an average of five 5) calls per hour during the same time period and follow an exponential distribution. a. Determine the probability that the CSR is idle. b. Determine the probability that three customers are in the system, waiting or being served c. Determine the average number of callers waiting for service on hold). d. Determine the average number of callers in the system. e. Determine the average time a caller spends waiting for service on hold). f. Determine the average time a caller spends in the system waiting time plus (service time). g. Determine the probability that an arriving call will have to wait for service.

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a. P0) = 1 - / = 1 - 4/5 = 0.20
b. P3) =...

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Question 3

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Which of the following variables is ordinarily not an output of waiting line analysis?

Since most service times follow an exponential distribution, there is no need to collect data on actual service times.

For the multiple-server queuing model to apply, k $\mu$ > $\lambda$ .

Discuss three categories of information necessary to analyze a waiting line.

____ is the process of a customer evaluating the waiting line and server system and deciding not to join the queue.

When $\lambda$ = $\mu$ , the operating characteristics are not defined, which means that these times and numbers of items grow infinitely large.

The multiple-server queuing model assumes jockeying can take place.

Rules that determine the order in which arrivals are sequenced through the service system are called

Discuss the seven key assumptions for the multiple-server waiting line model.

Which of the following is not a psychological strategy for dealing with a long wait-time?

A flower shop has one employee in the front of the store to sell flowers out of the cooler. On Saturdays customers arrive every six minutes, on average. The employee can serve a customer every five minutes, on average. The owner of the store feels that if there are more than four customers in the store at one time, additional customers may not come in because the wait appears too long. a. What is the chance of four or more customers being in the store at one time? b. What is the total time in minutes) a customer spends in the store? c. What is the average number of customers in the store?

Describe seven operating characteristics of a waiting line no formulas).

If the probability of no people waiting is 0.10, the probability of one person waiting is 0.09 and the probability of two people waiting is 0.08, what is the probability of three or more people waiting?

The mean arrival rate is used to express demand; the mean service rate is used to express a system's capacity.

A local hamburger chain is considering adding a drive-through window. They estimate that during the dinner hour, customer arrival rate will average 18 per hour and follow a Poisson distribution. Service times during this same period are estimated to follow an exponential distribution with a mean of 24 customers per hour. a. Determine the probability that the service facility drive-through window) is idle. b. Determine the probability of four vehicles in the system. c. Determine the average number of vehicles waiting for service. d. Determine the average number of vehicles in the system. e. Determine the average time a vehicle spends waiting for service. f. Determine the average time a vehicle spends in the system. g. Determine the probability that an arriving vehicle has to wait for service.

In queuing models, what are "channels"?

Many analytical queuing models exist, each based upon unique assumptions.

Arrival distributions for queuing models