Abstract
A queuing system is a process to measure the efficiency of a model by underlying the concepts of queue models: arrival and service time distributions, queue disciplines and queue behaviour. The main aim of this study is to compare the behaviour of a queuing system at check-in counters using the Queuing Theory Model and Fuzzy Queuing Model. The Queuing Theory Model gives performance measures of a single value while the Fuzzy Queuing Model has a range of values. The Dong, Shah and Wong (DSW) algorithm is used to define the membership function of performance measures in the Fuzzy Queuing Model. Based on the observation, the problem often occurs when customers are required to wait in the queue for a long time, thus indicating that the service systems are inefficient. Data including the variables were collected, such as arrival time in the queue (server) and service time. Results show that the performance measures of the Queuing Theory Model lie in the range of the computed performance measures of the Fuzzy Queuing Model. Hence, the results obtained from the Fuzzy Queuing Model are consistent to measure the queuing performance of an airline company in order to solve the problem in waiting line and will improve the quality of services provided by airline company.
Highlights
Queues happen at any place such as airport terminal, hospital, grocery store and even petrol station
The DSW algorithm fuzzy queuing model’s performance measure and the third is the comparison of both fuzzy queuing models
The result shows that the performance measures Lq, Ls, Wq and Ws for both Queuing Theory Model and Fuzzy Queuing Model were computed and compared
Summary
Queues happen at any place such as airport terminal, hospital, grocery store and even petrol station. Long queuing lines can be seen at an airport check-in counter especially during the arrival and departure of planes. The long queues may happen due to an insufficient service system and low service quality, increasing the waiting time. Reducing waiting time and providing quick service are very important in service-related operations [1]. Service-related companies place importance on reducing the waiting time of customers in order to increase customer satisfaction through improving their service quality. The queuing theory can be measured using the quantitative analysis technique to predict the characteristics of a waiting line [2]. The queuing theory is used to translate the customer’s arrival time as well as analyze the queuing behaviour mathematically from the amount of time that a customer needs to wait in the system based on a real queuing situation [3]
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