Optimality analysis for non-differentiable interval-valued optimization problems with fuzzy environment

This article explores optimality analysis in a fuzzy environment of non-differentiable interval-value optimization problems. Further, an approach is proposed for pseudoconvex optimization problems with general convex constraints. The concept of a (weak) non-dominated solution in the fuzzy sense for an interval optimization problem is inspired by the (weak) Pareto solution of a bi-objective optimization problem. Thus, we establish the optimality conditions of Karush-Kuhn-Tucker for a non-differentiable extremum problem of such a nature under the hypothesis of pseudoconvexity. In support of this, a bi-objective optimization problem is to be constructed for the corresponding non-differentiable fuzzy-valued optimization problem to prove these conditions. Numerical illustrations and simulation results from our learning are also provided in the paper.