An approach for linear programming under randomness and fuzziness: a case of discrete random variables with fuzzy probabilities
by Maged G. Iskander
International Journal of Operational Research (IJOR), Vol. 15, No. 2, 2012

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.

Online publication date: Sun, 11-Jan-2015

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