An interactive fuzzy satisficing method for multiobjective linear fractional programs with block angular structure

In this paper, we focus on multiobjective linear fractional programming problems with block angular structure. By considering the vague nature of human judgments, we assume that the decision maker may have a fuzzy goal for each of the objective functions. Having elicited the corresponding membership functions including nonlinear ones, if the decision maker specifies the reference membership values, the corresponding Pareto optimal solution can be obtained by solving the minimax problems for which the Dantzig-Wolfe decomposition method and Ritter's partitioning procedure are applicable. Then a linear programming-based interactive fuzzy satisficing method with decomposition procedures for deriving a satisficing solution for the decision maker efficiently from a Pareto optimal solution set is presented. An illustrative numerical example is provided to demonstrate the feasibility of the proposed method.