  Multi-variable nonlinear fuzzy optimization problem is considered under
linear order relation on fuzzy numbers. Using gH-differentiability of a
fuzzy-valued function $\tilde{f}$, new necessary and sufficient optimality
conditions are proposed. The optimality conditions are obtained without putting
additional conditions on fuzzy-valued functions like, convexity,
quasi-convexity, pseudo-convexity. Optimum solution of the fuzzy optimization
problem is obtained based on the optimality conditions. Illustrations and a
case study are given to explain the numerical applications of the proposed
results. Comparison of optimality conditions from existing literature is given.
