Question

Queuing Theory

Please provide short answers to the following questions below:

A.   How do we minimize reneging and balking?

B.   How do we determine acceptable wait time for customers, and what do we offer them (some strategies)? Note :( To find some solutions, it is important to consider the demand (what about it would be useful to understand)

C.   Why is most system that we examine will have an infinite call population?

D.   What is the effect of population being finite or infinite on queuing analysis?

Answer 1

A. Reneging is defined as the customer entering the line but leaving ti before being served. Balking is defined as customer deciding not to enter a waiting line. To minimize reneging, customers need to be engaged while they wait in queue. If customers are bored while waiting in the queue, they tend to leave. hence they need to be engaged in ways like signboards, entertainment etc. The checkout process also needs to be efficient so that customers who enter the queue, see that the queue is a moving queue and not a stangant queue. If the queue appears to be stagnant, customers tend to leave the queue. To prevent balking, ensure that the customers know beforehand how much time on an average they will spend waiting in the queue. Knowledge of wait time beforehand tend to make customer more probable to enter the queue. The time for which customers need to stand in the queue also can be reduced by ensuring that all the ancilliary tasks which the customer can do on his own are completed beforehand (for example web-checking compared to manual checking at airport counters).

B. To determine the acceptable wait time one can use the customer surveys. Customers need to be asked what is the average time they would wait in the queue. The surveys need to take into consideration various demographic and other factors like, time of the day, day of the week, gender of customers, age of customers, tyor of transaction etc so that the customers can be segregated into different groups as per their preference for waiting time. For example if it is found that customers are willing to wait for more time in a queue on weekends over weekdays, then we can employ a strategy to activate more counters on weekdays so that wait time is reduced. Similary if it is noted that customers with small order size tend to have a lesser acceptable wait time, then a separate counter can be dedicated to serve only those customers with a limit of order size so that they have a lesser wait time. Demand is also another criteria which is critical in determining the acceptable wait time. If the demand of the product or service is very high and the same cannot be serviced by any one or at anyplace else then customers will tend to have higher acceptable wait time. However if the product or a service is a commodity, then customers will tend to have lesser acceptable wait time in the queue. Hence it is critical to understand the demand for the product or service as well to determine the acceptable wait time. To give an illustration, if a person is applying for a visa, the person will tend to have a higher acceptable wait time as the demand for visa cannot be fulfilled by any other place than an embassy and the need for visa is high. Compared to this is a person is buying a candy at a departmental store then he or she will tend to have a lesser acceptable wait time as the criticality of demand is less and the same product will be available at multiple other places.

C. In infinite call population, we consider that the system is open. The arrival rate is not affected by the number of customers present in the system. New customers may enter the system any time while the exisitng customers leave the system as soon as they are served. In a finite calling population, however, the arrival rate is affected by the number of customers present in the system. In other words, in infinite calling population, there are always such a large number of potential customers so that there is one more customer who can arrive to be served. While in finite calling population, there are only a fixed number of customers, and there cannot be additions to the number of customers who are to be served. As most of the real world problems has non-countable potential customers (eg. bank, grocery stores, airort checking counters, ticketing counters etc.) in most system we examine infinite call population.

D. The most important effect of population being finite or infinite in queuing analysis is on the arrival rate of the system. In a finite population model, the arrival rate is affected by the population in the system. While in the infinite population model, the arrival rate is independent of the number of customers already present.