The waiting line or queue management is a critical part of service industry. It deals with issue of treatment of customers in sense reduce wait time and improvement of service. Queue management deals with cases where the customer arrival is random; therefore, service rendered to them is also random.
A service organization can reduce cost and thus improve profitability by efficient queue management. A cost is associated with customer waiting in line and there is cost associated with adding new counters to reduce service time. Queue management looks to address this trade off and offer solutions to management.
Waiting in line is common phenomena in daily life, for example, banks have customers in line to get service of teller, cars queue up for re-filling, workers line up to access machine to complete their job. Therefore, management needs to work on formulae, which will reduce wait time and create delighted customers without incurring an additional cost. Generally, queue management problems are trade offs situation between cost of time spent in waiting v/s cost of additional capacity or machinery.
In a waiting line scenario, there are cases of finite population of customers and infinite population of customers.
A finite population scenario considers a fixed or limited size of customers visiting the service counter. It also assumes that customer once served will leave the line thus reducing overall population of customers. However finite population model also considers a scenario where the customer after getting served will re-visit the service counter for re-service, leading to increase in finite population.
An infinite population theory looks at a scenario where subtractions and addition of customer do not impact overall workability of the model.
To solve problems related to queue management it is important to understand characteristics of the queue. Some common queue situations are waiting in line for service in super-market or banks, waiting for results from computer and waiting in line for bus or commuter rail. General premise of queue theory is that there are limited resources for a given population of customers and addition of a new service line will increase the cost aspect to the business. A typical queue system has the following:
Arrival Process: As the name suggests an arrival process look at different components of customer arrival. Customer arrival could in single, batch or bulk, arrival as distribution of time, arrival in finite population or infinite population.
Service Mechanism: this looks at available resources for customer service, queue structure to avail the service and preemption of service. Underlining assumption here is that service time of customers is independent of arrival to the queue.
Queue Characteristics: this looks at selection of customers from the queue for service. Generally, customer selection is through first come first served method, random or last in first out. As a result, customers leave if the queue is long, customer leave if they have waited too long or switch to faster serving queue.
Another aspect of waiting line management is the service configuration. There are four types of service configuration, and they are as follows: