Quadratic fuzzy bilevel chance constrained programming with parameters following Weibull distribution

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Abstract

This paper presents a fuzzy goal programming approach for solving quadratic fuzzy bilevel programming problems with probabilistic constraints containing Weibull distributed fuzzy random variables. In the proposed methodology the problem is first converted into an equivalent quadratic fuzzy bilevel programming model by applying chance constrained programming technique developed with the use of α -cuts in a fuzzily defined stochastic decision making situation. Then the developed model is transferred into an equivalent deterministic one by using the method of defuzzification based on probability density function of the corresponding membership functions. The individual optimal value of the objective of each decision makers is found in isolation to construct the quadratic fuzzy membership goals of each of the decision makers. The quadratic membership goals are then converted into linear goals by applying approximation techniques. A weighted minsum goal programming method is then applied to achieve the highest membership degree of each of the membership goals of decision makers in the decision making context. Finally a comparison is made on the applied approximation techniques with the help of using distance function. An illustrative numerical example is provided to demonstrate the applicability of the proposed methodology. © 2013 Springer International Publishing.

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APA

Biswas, A., & Kumar De, A. (2013). Quadratic fuzzy bilevel chance constrained programming with parameters following Weibull distribution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8298 LNCS, pp. 406–418). https://doi.org/10.1007/978-3-319-03756-1_37

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