Computational methods for two-level linear programming problems with fuzzy parameters through genetic algorithms

From the observation that possible values of parameters involved in objective functions and constraints of mathematical programming problems are often only imprecisely or ambiguously known to experts, we consider two-level linear programming problems with fuzzy parameters represented by fuzzy numbers. A computational method, which is based on genetic algorithms, for obtaining the Stackelberg solution to the two-level linear programming problem with fuzzy parameters is developed. To demonstrate the efficiency of the proposed computational method, computational experiments are carried out.