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Monte Carlo methods in fuzzy queuing theory

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Abstract

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.

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Authors and Affiliations

  1. Department of Mathematics, University of Alabama at Birmingham, Birmingham, AL, 35294, USA

    Areeg Abdalla & James J. Buckley

Authors
  1. Areeg Abdalla
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  2. James J. Buckley
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Correspondence to James J. Buckley.

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Abdalla, A., Buckley, J.J. Monte Carlo methods in fuzzy queuing theory. Soft Comput 13, 1027–1033 (2009). https://doi.org/10.1007/s00500-008-0376-y

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  • DOI: https://doi.org/10.1007/s00500-008-0376-y

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