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Solving fuzzy problems in operations research: inventory control

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Abstract

 In this paper we are interested in generating good approximate solutions to single item, N-period, fuzzy inventory control problems. It is a fuzzy inventory control problem since some of the parameters (ordering cost, holding cost, penalty cost) can be fuzzy numbers. We consider three cases: (1) demand is known each period; (2) demand is unknown, and fuzzy each period; and (3) demand is fuzzy and backordering is allowed. We employ an evolutionary algorithm to search out good approximate solutions.

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Authors and Affiliations

  1. Department of Mathematics, University of Alabama at Birmingham, Birmingham, Alabama, 35294, USA e-mail: buckley@math.uab.edu, , , , , , US

    J. J. Buckley

  2. Department of Electrical Engineering and Computer Science, University of Siegen, Hölderlinstr. 3, 57068 Siegen, Germany, , , , , , DE

    T. Feuring

  3. Department of Computer Science, Meiji University, 1-1-1 Higashimita, Tama-ku, Kawasaki, 214-8571, Japan, , , , , , JP

    Y. Hayashi

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  1. J. J. Buckley
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  2. T. Feuring
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  3. Y. Hayashi
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Buckley, J., Feuring, T. & Hayashi, Y. Solving fuzzy problems in operations research: inventory control. Soft Computing 7, 121–129 (2002). https://doi.org/10.1007/s00500-002-0180-z

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  • DOI: https://doi.org/10.1007/s00500-002-0180-z

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