Queuing models are concerned with balancing the cost of waiting in the queue with the:
Answer(s): A
Queuing waiting-line) models minimize, for a given rate of arrivals, the sum of 1) the cost of providing service including facility costs and operating costs) and 2) the cost of idle resources waiting in line. The latter may be a direct cost, if paid employees are waiting, or an opportunity cost in the case of waiting customers. This minimization occurs at the point where the cost of waiting is balanced by the cost of providing service.
The operating condition that car-or-mot be identified by using a queuing model is the:
Answer(s): C
Queuing models determine the operating characteristics of a waiting line: the probability that no units are in the system, the average units in the line, the average units in the system, the average time a unit waits, the average time a unit is in the system, the probability that a unit must wait, and the probability of a given number of units in the system. However, the actual time spent in the queue cannot be determined from the model.
A bank has changed from a system in which lines are formed in front of each teller - to a one line, multiple-server system.When a teller is free, the person at the head of the line goes to that teller. Implementing the new system will:
Answer(s): B
When all customers must wait in a single queue, a decrease in waiting time is possible given multiple servers. An added effect is to increase customer satisfaction.
The drive-through service at a fast-food restaurant consists of driving up to place an order, advancing to a window to pay for the order, and then advancing to another window to receive the items ordered. This type of waiting-line system is:
The drive-through represents a single queue channel). Because this waiting line has three services in series, it may be said to be multiple phase. Another example is the typical factory assembly line. This terminology channel, phase), however, is not used by all writers on queuing theory.
A post office serves customers in a single line at one service window. During peals periods, the rate of arrivals has a Poisson distribution with an average of 100 customers per hour and service times that are exponentially distributed with an average of 0 seconds per customer.From this, one can conclude that the:
One hundred customers arrive in line per hour and only 60 are serviced per hour. Accordingly, the queue will expand to infinity during peaty periods.
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