Question 1) A goal of many waiting line problems is to help a firm find the idea

1) A goal of many waiting line problems is to help a firm find the ideal level of services that minimize the cost of waiting and the cost of providing the service.

2) One difficulty in waiting line analysis is that it is sometimes difficult to place a value on customer waiting time.

3) The goal of most waiting line problems is to identify the service level that minimizes service cost.

4) Two characteristics of arrivals are the line length and queue discipline.

5) Limited calling populations are assumed for most queuing models.

6) An “infinite calling population” occurs when the likelihood of a new arrival depends upon the number of past arrivals.

7) On a practical note — if we were to study the waiting lines in a hair salon that had only five chairs for patrons waiting, we should use an infinite queue waiting line model.

8) If we are studying the arrival of automobiles at a highway toll station, we can assume an infinite calling population.

9) When looking at the arrivals at the ticket counter of a movie theater, we can assume an unlimited queue.

10) Arrivals are random when they are dependent on one another and can be predicted.

11) On a practical note — if we are using waiting line analysis to study customers calling a telephone number for service, balking is probably not an issue.

12) On a practical note — if we are using waiting line analysis to study cars passing through a single tollbooth, reneging is probably not an issue.

13) On a practical note — we should probably view the checkout counters in a grocery store as a set of single channel systems.

14) A bank with a single queue to move customers to several tellers is an example of a single-channel system.

15) Service times often follow a Poisson distribution.

16) An M/M/2 model has Poisson arrivals exponential service times and two channels.

17) In a single-channel, single-phase system, reducing the service time only reduces the total amount of time spent in the system, not the time spent in the queue.

18) The wait time for a single-channel system is more than twice that for a two-channel system using two servers working at the same rate as the single server.

19) The study of waiting lines is called queuing theory.

20) The three basic components of a queuing process are arrivals, service facilities, and the actual waiting line.

21) In the multichannel model (M/M/m), we must assume that the average service time for all channels is the same.

22) Queuing theory had its beginning in the research work of Albert Einstein.

23) The arrivals or inputs to the system are sometimes referred to as the calling population.

24) Frequently in queuing problems, the number of arrivals per unit of time can be estimated by a probability distribution known as the Poisson distribution.

25) An automatic car wash is an example of a constant service time model.

26) Balking customers are those who enter the queue but then become impatient and leave without completing the transaction.

27) In a constant service time model, both the average queue length and average waiting time are halved.

28) A hospital ward with only 30 beds could be modeled using a finite population model.

29) A finite population model differs from an infinite population model because there is a random relationship between the length of the queue and the arrival rate.

30) A transient state is the normal operating condition of the queuing system.

31) A queue system is in a transient state before the steady state is reached.

32) Little’s Flow Equations are applicable for single-channel systems only.

33) Little’s Flow Equations are advantageous because if one characteristic of the operating system is known, the other characteristics can be easily found.

34) Using a simulation model allows one to ignore the common assumptions required to use analytical models.

35) If we are using a simulation queuing model, we still have to abide by the assumption of a Poisson arrival rate, and negative exponential service rate.

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