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Production Engineering and Management under Fuzziness pp 249–277Cite as

Fuzzy Simulation and Optimization of Production and Logistic Systems

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 252))

Abstract

The basic paradigm for simulation of production and logistic systems is the probabilistic approach to describing the real world uncertainty. However, in many cases we do not have the information that would be precise enough to build corresponding probabilistic models or there are some human factors preventing doing so. In such situations, the mathematical tools of fuzzy sets theory may be successfully used. It seems that a simple and natural way to do this is the replacement of probability densities with appropriate fuzzy intervals and the use of fuzzy arithmetic to build adequate fuzzy models. Since the models of production and logistic systems are usually used for the optimization of simulated processes, the problem of fuzzy optimization arises. The problems of simulation and optimization in the fuzzy setting can be solved with use of fuzzy and interval arithmetic, but there are some inherent problems in formulation of basic mathematical operations on fuzzy and interval objects. The more important of them (especially for the fuzzy optimization) is the interval and fuzzy objects comparison. The paper presents a new method for crisp and fuzzy interval comparison based on the probabilistic approach. The use of this method in the synthesis with α-cut representation of fuzzy values and usuall interval arithmetic rules, makes it possible to develope an affective approach to fuzzy simulation and optimization. This approach is illustrated by the examples of fuzzy simulation of linear production line and logistic system and by the example of fuzzy solution of optimal goods distribution problem. The results obtained with use of the proposed approach are compared with those obtained using Monte-Carlo method.

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Authors and Affiliations

  1. Institute of Comp. & Information Sci., Czestochowa University of Technology, Dabrowskiego 73, 42-200, Czestochowa, Poland

    L. Dymowa & P. Sevastjanov

Authors
  1. L. Dymowa
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  2. P. Sevastjanov
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Editor information

Editors and Affiliations

  1. Management Faculty, Department of Industrial Engineering, Istanbul Technical University, Macka, 34367, Istanbul, Turkey

    Cengiz Kahraman

  2. Harry f. Byrd, Jr. School of Business, Shenandoah University, 1460 University Dr., 22601, Winchester, VA, USA

    Mesut Yavuz

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Dymowa, L., Sevastjanov, P. (2010). Fuzzy Simulation and Optimization of Production and Logistic Systems. In: Kahraman, C., Yavuz, M. (eds) Production Engineering and Management under Fuzziness. Studies in Fuzziness and Soft Computing, vol 252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12052-7_11

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  • DOI: https://doi.org/10.1007/978-3-642-12052-7_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12051-0

  • Online ISBN: 978-3-642-12052-7

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