Otimização multiobjetivo em redes de filas

Abstract

In one of the most challenging finite queueing network optimization problems, the number of buffers (f1) and the overall service rate (f2) must be reduced while the throughput (f3) must be maximized. In order to meet these three conicting objectives (min f1, min f2, and max f3), a multiobjective genetic algorithm was developed specially for acyclic general-service queueing networks. The proposed method is shown to produce a set of efficient solutions for the three objectives f1, f2, and f3. In order to determine the efficacy of the proposed approach, a comprehensive set of computational experiments was conducted and analyzed. The insights obtained from the analysis of some queueing networks may be helpful to practitioners and scientists in the complex task of analyzing and planning general-service time queueing acyclicnetworks.