Planning and Forecasting With Robust Dynamic Models

Abstract

This paper deals with a defuzzification technique for dynamic models formulated with linguistic variables. The theorem of representation is applied in order to obtain a family of crisp models. This technique is particularly suitable for dynamic linear programming models, where the coefficients are fuzzy sets or fuzzy numbers.