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Springer Handbook of Computational Intelligence pp 131–143Cite as

Fuzzy Linear Programming and Duality

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Abstract

The chapter is concerned with linear programming problems whose input data may be fuzzy while the values of variables are always real numbers. We propose a rather general approach to these types of problems, and present recent results for problems in which the notions of feasibility and optimality are based on the fuzzy relations of possibility and necessity. Special attention is devoted to the weak and strong duality.

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Abbreviations

FLP:

fuzzy linear programming

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Author information

Authors and Affiliations

  1. Dep. Informatics and Mathematics, Silesian University in Opava, University Sq. 1934/3, 73340, Karviná, Czech Republic

    Jaroslav Ramík

  2. Theoretical Computer Science and Mathematical Logic, Charles University, Malostranské náměstí 25, 118 00, Prague, Czech Republic

    Milan Vlach

Authors
  1. Jaroslav Ramík
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  2. Milan Vlach
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Corresponding author

Correspondence to Jaroslav Ramík .

Editor information

Editors and Affiliations

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

    Janusz Kacprzyk

  2. Dep. Electrical and Computer Engineering, University of Alberta, 116 Street 9107, T6J 2V4, Edmonton, Alberta, Canada

    Witold Pedrycz

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Ramík, J., Vlach, M. (2015). Fuzzy Linear Programming and Duality. In: Kacprzyk, J., Pedrycz, W. (eds) Springer Handbook of Computational Intelligence. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43505-2_8

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  • DOI: https://doi.org/10.1007/978-3-662-43505-2_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-43504-5

  • Online ISBN: 978-3-662-43505-2

  • eBook Packages: EngineeringEngineering (R0)

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