Solving Fuzzy Quadratic Programming Problems with a Proposed Algorithm

Abstract

The theory of fuzzy mathematics has been proven very effective for defining and solving optimization problems. Fuzzy quadratic programming (FQP) is a consequence of this approach. In this paper, an algorithm has been proposed to solve FQP with coefficients as triangular fuzzy numbers (TFN). The proposed algorithm converts FQP into two parametric quadratic programming (QP) problems. These QP solutions provide a lower and upper bound on the objective function of FQP. When these two values coincide, an optimal solution is achieved. This algorithm has been analyzed using a numerical example and compared with existing methods.