A new approach to fuzzy optimization is proposed. It is based on application of approximate reasoning categories in order to obtain a more flexible representation of logical aggregation and defuzzification. It allows to design a non-iterative algorithm for fuzzy optimization which surpass the well-known Zimmermann's approach. Bellman-Zadeh' s method can be considered as a special case of the approach proposed here. An illustrative example is presented.