%0 Journal Article
%T Solving a non-convex non-linear optimization problem constrained by fuzzy relational equations and Sugeno-Weber family of t-norms
%J Journal of Algorithms and Computation
%I University of Tehran
%Z 2476-2776
%A Ghodousian, Amin
%A Ahmadi, A.
%A Dehghani, A.
%D 2017
%\ 12/01/2017
%V 49
%N 2
%P 63-101
%! Solving a non-convex non-linear optimization problem constrained by fuzzy relational equations and Sugeno-Weber family of t-norms
%K Fuzzy relational equations
%K nonlinear optimization
%K genetic algorithm
%R 10.22059/jac.2017.7978
%X Sugeno-Weber family of t-norms and t-conorms is one of the most applied one in various fuzzy modelling problems. This family of t-norms and t-conorms was suggested by Weber for modeling intersection and union of fuzzy sets. Also, the t-conorms were suggested as addition rules by Sugeno for so-called $\lambda$–fuzzy measures. In this paper, we study a nonlinear optimization problem where the feasible region is formed as a system of fuzzy relational equations (FRE) defined by the Sugeno-Weber t-norm. We firstly investigate the resolution of the feasible region when it is defined with max-Sugeno-Weber composition and present some necessary and sufficient conditions for determining the feasibility of the problem. Also, two procedures are presented for simplifying the problem. Since the feasible solutions set of FREs
%U https://jac.ut.ac.ir/article_7978_699476726464c0890fc1bd731369b4c2.pdf