A new methodology for crisp equivalent of fuzzy chance constrained programming problem

This paper deals with a chance constrained programming model, where both fuzziness and randomness are present in the objective function and constraints. The concept of fuzzy random variable, mean and variance of fuzzy random variable, minimum of fuzzy numbers are used in the model. The methodology i...

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Published in:Fuzzy optimization and decision making Vol. 7; no. 1; pp. 59 - 74
Main Authors: Nanda, S., Panda, G., Dash, J. K.
Format: Journal Article
Language:English
Published: Boston Springer US 01.03.2008
Springer Nature B.V
Subjects:
Artificial Intelligence
Calculus of Variations and Optimal Control; Optimization
Decision making
Expected values
Fuzzy logic
Fuzzy sets
Mathematical Logic and Foundations
Mathematical programming
Mathematics
Mathematics and Statistics
Normal distribution
Numbers
Operations Research/Decision Theory
Optimization
Probability
Probability distribution
Probability Theory and Stochastic Processes
Random variables
Studies
Fuzzy mean
Fuzzy variance
Fuzzy chance constrained programming problem
Fuzzy random variable
Fuzzy normal distribution
Minimum of fuzzy numbers
ISSN:1568-4539, 1573-2908
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Abstract This paper deals with a chance constrained programming model, where both fuzziness and randomness are present in the objective function and constraints. The concept of fuzzy random variable, mean and variance of fuzzy random variable, minimum of fuzzy numbers are used in the model. The methodology is verified through a numerical example.
AbstractList This paper deals with a chance constrained programming model, where both fuzziness and randomness are present in the objective function and constraints. The concept of fuzzy random variable, mean and variance of fuzzy random variable, minimum of fuzzy numbers are used in the model. The methodology is verified through a numerical example.
This paper deals with a chance constrained programming model, where both fuzziness and randomness are present in the objective function and constraints. The concept of fuzzy random variable, mean and variance of fuzzy random variable, minimum of fuzzy numbers are used in the model. The methodology is verified through a numerical example. [PUBLICATION ABSTRACT]
Author Dash, J. K.
Nanda, S.
Panda, G.
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  fullname: Panda, G.
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  givenname: J. K.
  surname: Dash
  fullname: Dash, J. K.
  organization: Department of Mathematics, Indian Institute of Technology
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Cites_doi 10.1016/S0165-0114(96)00236-9
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Issue 1
Keywords Fuzzy mean
Fuzzy variance
Fuzzy chance constrained programming problem
Fuzzy random variable
Fuzzy normal distribution
Minimum of fuzzy numbers
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PublicationSubtitle A Journal of Modeling and Computation Under Uncertainty
PublicationTitle Fuzzy optimization and decision making
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  issue: 2
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  publication-title: Fuzzy Optimization and decision making
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  publication-title: Fuzzy Sets.S
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  year: 2004
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  publication-title: Fuzzy Sets and Systems
  doi: 10.1016/0165-0114(92)90256-4
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Snippet This paper deals with a chance constrained programming model, where both fuzziness and randomness are present in the objective function and constraints. The...
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SubjectTerms Artificial Intelligence
Calculus of Variations and Optimal Control; Optimization
Decision making
Expected values
Fuzzy logic
Fuzzy sets
Mathematical Logic and Foundations
Mathematical programming
Mathematics
Mathematics and Statistics
Normal distribution
Numbers
Operations Research/Decision Theory
Optimization
Probability
Probability distribution
Probability Theory and Stochastic Processes
Random variables
Studies
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Title A new methodology for crisp equivalent of fuzzy chance constrained programming problem
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