Working Paper 04-69 Statistics and Econometrics Series 17 December 2004 Departamento de Estadística Universidad Carlos III de Madrid Calle Madrid, 126 28903 Getafe (Spain) Fax (34) 91 624-98-49 BAYESIAN CONTROL OF THE NUMBER OF SERVERS IN A GI/M/C QUEUING SYSTEM María Concepción Ausín Olivera; Rosa Elvira Lillo; Michael Peter Wiper* Abstract In this paper we consider the problem of designing a GI/M/c queueing system. Given arrival and service data, our objective is to choose the optimal number of servers so as to minimize an expected cost function which depends on quantities, such as the number of customers in the queue. A semiparametric approach based on Erlang mixture distributions is used to model the general interarrival time distribution. Given the sample data, Bayesian Markov chain Monte Carlo methods are used to estimate the system parameters and the predictive distributions of the usual performance measures. We can then use these estimates to minimize the steady-state expected total cost rate as a function of the control parameter c. We provide a numerical example based on real data obtained from a bank in Madrid. Keywords: Queueing systems, Bayesian design, birth-and-death MCMC, optimal service channels. * Ausín Departamento de Estadística y Econometría, Universidad Carlos III de Madrid, C/ Madrid 126, 28903 Getafe (Madrid), Spain, e-mail: concepcion.ausin@uc3m.es; Lillo, Departamento de Estadística y Econometría, Universidad Carlos III de Madrid, Tfno: 91-6249857, e-mail: rosa.lillo@uc3m.es; Wiper, Departamento de Estadística y Econometría, Universidad Carlos III de Madrid, Tfno: 91-6249852, e- mail: michael.wiper@uc3m.es.