Characterization of the stability set for non-differentiable fuzzy parametric optimization problems | Zendy

Mohamed Abd El-Hady Kassem | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Characterization of the stability set for non-differentiable fuzzy parametric optimization problems

Author(s) -

Mohamed Abd El-Hady Kassem

Publication year - 2005

Publication title -

international journal of mathematics and mathematical sciences

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.21

H-Index - 39

eISSN - 1687-0425

pISSN - 0161-1712

DOI - 10.1155/ijmms.2005.1995

Subject(s) - mathematics , differentiable function , parametric programming , parametric statistics , nonlinear programming , mathematical optimization , pareto principle , characterization (materials science) , fuzzy logic , stability (learning theory) , set (abstract data type) , fuzzy set , nonlinear system , fuzzy number , computer science , pure mathematics , artificial intelligence , statistics , machine learning , physics , materials science , quantum mechanics , programming language , nanotechnology

This note presents the characterization of the stability set of the first kind for multiobjective nonlinear programming (MONLP) problems with fuzzy parameters either in the constraints or in the objective functions without any differentiability assumptions. These fuzzy parameters are characterized by triangular fuzzy numbers (TFNs). The existing results concerning the parametric space in convex programs are reformulated to study for multiobjective nonlinear programs under the concept of ÃŽÂ±-Pareto optimality

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research