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  • Data may be fuzzy while the values of variables are always real numbers. We propose rather general approach to this type 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.
  • Data may be fuzzy while the values of variables are always real numbers. We propose rather general approach to this type 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. (en)
  • Data may be fuzzy while the values of variables are always real numbers. We propose rather general approach to this type 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. (cs)
Title
  • Fuzzy linear programming and duality
  • Fuzzy linear programming and duality (en)
  • Fuzzy linear programming and duality (cs)
skos:prefLabel
  • Fuzzy linear programming and duality
  • Fuzzy linear programming and duality (en)
  • Fuzzy linear programming and duality (cs)
skos:notation
  • RIV/61988987:17610/15:A15017T1!RIV15-MSM-17610___
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  • P(ED1.1.00/02.0070)
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  • 163
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  • RIV/61988987:17610/15:A15017T1
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  • linear programming; fuzzy linear programming; fuzzy optimization; duality (en)
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  • [937A68A7E63A]
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  • Berlin, Heidelberg, New York
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  • Handbook o Computational Intelligence
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  • Vlach, Milan
  • Ramík, Jaroslav
number of pages
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  • Springer-Verlag
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  • 978-3-662-43504-5
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  • 17610
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