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A New Approach to Fuzzy Constraints in Linear Programming

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Neural Networks and Soft Computing

Part of the book series: Advances in Soft Computing ((AINSC,volume 19))

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Abstract

In the article it is described a new proposal of the transformation of fuzzy constraints in linear programming problem with fuzzy coefficients for hard constraints using triparametric approach. As regards constraint coefficients, it is assumed that they are flat fuzzy numbers on the L-R representation. The method is a trial of generalization of possibilistic approach based on the Zadeh’s extension principle so that the nature of interpretation of fuzzy inequality can be graduated from the most optimistic to the most pessimistic interpretation. The proposed parameters of feasibility enable the person who decides to differentiate preferences in relation to particular constraints.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science & Information Systems, Technical University of Szczecin, 49, Żołnierska st., 71-210, Szczecin, Poland

    Joanna Banaś

Authors
  1. Joanna Banaś
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Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Technical University Częstochowa, Al. Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski

  2. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

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© 2003 Springer-Verlag Berlin Heidelberg

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Banaś, J. (2003). A New Approach to Fuzzy Constraints in Linear Programming. In: Rutkowski, L., Kacprzyk, J. (eds) Neural Networks and Soft Computing. Advances in Soft Computing, vol 19. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1902-1_40

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  • DOI: https://doi.org/10.1007/978-3-7908-1902-1_40

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-0005-0

  • Online ISBN: 978-3-7908-1902-1

  • eBook Packages: Springer Book Archive

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