Question 14.1 A goal of many waiting line problems is to help a firm find th

14.1 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.

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

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

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

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14.5 Limited calling populations are assumed for most queuing models.

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

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14.7 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.

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

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

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

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14.11 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.

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14.12 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.

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

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

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14.15 Service times often follow a Poisson distribution.

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

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14.17 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.

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14.18 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.

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14.19 The study of waiting lines is called queuing theory.

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

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

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

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

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

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