This paper presents a methodology for the efficient solution of fuzzy optimization problems. Design variables, as well as system parameters are modeled as fuzzy numbers characterized by membership functions. An optimization approach based on approximation concepts is introduced. High quality approximations for system response functions are constructed using the concepts of intermediate response quantities and intermediate variables. These approximations are used to replace the solution of the original problem by a sequence of approximate problems. Optimization techniques for non-differentiable problems which arise in fuzzy optimization are used to solve the approximate optimization problems. Example problems are presented to illustrate the ideas set forth.