Design of a fuzzy finite capacity queuing model based on the degree of customer satisfaction: Analysis and fuzzy optimization
Due to uncontrollable factors, the parameters in the queuing models may be uncertain and so in this paper we present the design of a fuzzy finite capacity queuing model in which the arrival pattern and the service pattern follow an exponential distribution under uncertain parameter. As for the design of the system, the criterion of optimization proposed is aimed at the optimum selection of the number of servers, with the goal of providing a high degree of satisfaction to clients when they join the system. This optimization process will be solved through Markov chains with fuzzy state. The validity of the procedure proposed to incorporate fuzzy data in this queuing system is confirmed by a fuzzy simulation experiment of the differential equations, which govern the behaviour of the model, by the Bontempi's Qua. Si. III algorithm. The extension of queuing decision models to fuzzy environments enables the decision maker to obtain more informative results and wider knowledge on the behaviour of the system, since the results obtained in the fuzzy queuing model are fuzzy subsets containing the whole initial information; that is why the finite capacity queuing models with uncertain data can have a broader range of applications. (C) 2008 Elsevier B.V. All rights reserved.
finite capacity queuing model markov chain with fuzzy states fuzzy simulation fuzzy system model