An effective solution approach to fuzzy programming with application to project scheduling

In the present paper, a novel solution approach is proposed for a class of fuzzy programming models. In this direction, we prove that the lower and upper bounds of their fuzzy optimal objective values at a possibility level, α∈ [0 , 1] , can be calculated solving a pair of crisp mathematical programming models. Thus, their membership functions are simulated enumerating the upper and lower bounds obtained from a series of α-level calculations. Motivated from real-world project scheduling applications, several numerical examples are considered to evaluate the accuracy, efficiency and applicability of our treatment. The results derived are compared with those of Chen and Tsai (Eur J Oper Res 212(2):386–397, 2011) to demonstrate that our method is easier to be utilized, with lower computational complexity, nonetheless without losing its effectiveness. Finally, the new approach does not suffer from the limitation to be applicable only to linear programming models that makes it suitable for a wider range of models and applications.