A novel approach for optimization in a fuzzy finite capacity queuing model with system cost and expected degree of customer satisfaction

• Published in: Decision Science Letters Vol. 4; no. 4; pp. 487 - 496
• Main Authors: Shahin, Mohammad Bagher, Doniavi, Ali, Solimanpur, Maghsoud, Shahin, Mahdi
• Format: Journal Article
• Language: English
• Published: Growing Science 01.09.2015
• Subjects: Expected degree of customer satisfaction; Finite-capacity queuing model; Optimal number of servers; Productivity rate index; System cost
• ISSN: 1929-5804; 1929-5812
• DOI: 10.5267/j.dsl.2015.6.001

From a wide variety of queuing models, the finite-capacity queuing models are the most commonly used, where arrival and service rates follow an exponential distribution. Based on two criteria of system cost and expected degree of customer satisfaction, the present study defines a new productivity rate index and evaluates the optimization of a queuing model with finite capacity. In queuing models, obviously, as the number of servers increases, the length of waiting lines decreases, the expected degree of customer satisfaction enhances, and obviously the system cost increases. This study deals with the mathematical relationships involved in the computations of these two criteria, and proposes a novel approach to determine an optimal number of servers by considering a decision-maker's priority and establishing a trade-off between criteria.