A New Branch and Reduce Approach for Solving Generalized Linear Fractional Programming

摘要

In this paper, for solving generalized linear fractional programming (GLFP), a new branch-and-reduce approach is presented. Firstly, an equivalent problem (EP) ofGLFP is given; then, a new linear relaxation technique isproposed; finally, the problem EP is reduced to a sequenceof linear programming problems by using the new linearrelaxation technique. Meanwhile, to improve the convergencespeed of our algorithm, two reducing techniques are presented.The proposed algorithm is proved to be convergent, and someexperiments are provided to show its feasibility and efficiency.