1996 Volume 8 Issue 6 Pages 1125-1133
In this paper, we discuss a soft optimal solution which is robust against the fluctuations of the objective coefficient values in the setting of the linear programming problem. A soft optimal solution stands for a feasible solution whose objective function value is near the optimal value of the linear programming problem. The ambiguity of the objective coeffcient values is represented by possibility distributions. In order to express the nearness of the objective function value, we introduce a fuzzy goal defined on the deviation from the optimal value. A necessity measure is adopted for representing the robustness and a necessarily fuzzy optimal solution set is defined. The solution having the highest membership value of the necessarily fuzzy optimal solution set can be considered as the most reasonable solution and called the best necessarily fuzzy optimal solution. A method of the best necessarily fuzzy optimal solution is proposed.
