Monte Carlo methods in fuzzy queuing theory

Research paper by Areeg Abdalla, James J. Buckley

Indexed on: 25 Oct '08Published on: 25 Oct '08Published in: Soft Computing


In this paper, we consider an optimization problem in fuzzy queuing theory that was first used in web planning. This fuzzy optimization problem has no solution algorithm and approximate solutions were first produced by computing the fuzzy value of the objective function for only sixteen values of the fuzzy variables. We introduce our fuzzy Monte Carlo method, using a quasi-random number generator, to produce 100,000 random sequences of fuzzy vectors for the fuzzy variables, which will present a much better approximate solution.