This approach is firstly introduced at 2012 by Pishvaee, Razmi & Torabi[1] in the Journal of Fuzzy Sets and Systems.
ROFP enables the decision makers to be benefited from the capabilities of both fuzzy mathematical programming and robust optimization approaches.
At 2016 Pishvaee and Fazli[2] put a significant step forward by extending the ROFP approach to handle flexibility of constraints and goals.
From another point of view, it can be said that different ROFP models developed in the literature can be classified in three categories according to degree of conservatism against uncertainty.
Regarding the optimality robustness, this method minimizes the worst possible value of objective function (min-max logic).