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Floudas C.A., Pardalos P., Adjiman C., Esposito W.R., Gumus Z.H., Harding S.T., Klepeis J.L., Meyer C.A. and Sshweiger, C.A. (1999) Handbook of Test Problems in Local and Global Optimization. Non convex Optimization and its Applications, Vol. 33, Kluwer Academic Publishers, Dordrecht.

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• TITLE: A Quadratic Programming with Triangular Fuzzy Numbers

  AUTHORS: Seyedeh Maedeh Mirmohseni, Seyed Hadi Nasseri

  KEYWORDS: Fuzzy Numbers, Quadratic Programming, Membership Function

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.5 No.11, November 23, 2017

  ABSTRACT: Quadratic Programming (QP) is a mathematical modeling technique designed to optimize the usage of limited resources and has been widely applied to solve real world problems. In conventional quadratic programming model the parameters are known constants. However in many practical situations, it is not reasonable to require that the constraints or the objective function in quadratic programming problems be specified in precise, crisp terms. In such situations, it is desirable to use some type of Fuzzy Quadratic Programming (FQP) problem. In this paper a new approach is proposed to derive the fuzzy objective value of fuzzy quadratic programming problem, where the constraints coefficients and the right-hand sides are all triangular fuzzy numbers. The proposed method is solved using MATLABTM toolbox and the numerical results are presented.