Solving fuzzy linear programming problems with Interval Type-2 RHS
Published 1 October 2009
Juan Carlos Figueroa–García
Citations31
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TL;DR
In this paper, a LP problem with uncertain right side parameters treated as interval type-2 fuzzy sets is solved by two optimization strategies: the first is a type-reduction method and the second one is a pre-defuzzified ¿ - cut approach.
Abstract
This paper presents two general methods to handle uncertainties in the right hand side parameters of a linear programming (LP) model by means of interval type-2 fuzzy sets (IT2 FS). In this paper, a LP problem with uncertain right side parameters treated as interval type-2 fuzzy sets is solved by two optimization strategies: The first one is a type-reduction method and the second one is a pre-defuzzified ¿ - cut approach. After the IT2 FS inference process, a real-valued solution must be found. In this way two methods based on classical optimization routines are presented to obtain optimal solutions when uncertain right hand side parameters exist.
Keywords
Decision SciencesMathematicsEngineering
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