An approach for linear programming under randomness and fuzziness: a case of discrete random variables with fuzzy probabilities

Maged G. Iskander

International Journal of Operational Research, 2012, vol. 15, issue 2, 215-225

Abstract: This paper presents a new approach for solving stochastic fuzzy linear programming problems. The random variables in the constraints and in the objective function are discrete with triangular fuzzy probabilities. The α-cut method is applied to the triangular membership functions of the fuzzy probabilities. For the constraints, the chance-constrained approach is utilised, whether according to strict dominance relation or dominance relation. The mean-variance criterion is exploited in the objective function, whereas four different cases are considered. The model, for the general case, which takes the form of mixed zero-one non-linear programme, is illustrated by a numerical example.

Keywords: stochastic fuzzy programming; discrete random variables; fuzzy probabilities; chance-constrained approach; mean variance criterion; chance constraints; stochastic programming. (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:15:y:2012:i:2:p:215-225

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