Global Optimization Algorithm for Generalized Linear Fractional Programming Problems

In this paper a branch and bound algorithm is proposed for obtaining global minimum of generalized linear fractional progamming problems. By utilizing linearization technique and equivalent problem the relaxation linear programming (RLP) of the original problem (P) is established. The proposed algorithm is convergent to the global minimum of (P) through the successive refinement of linear relaxation of the feasible region of objective function and solutions of a series of (RLP). And finally the numerical examples are given to illustrate the feasibility of the presented algorithm.