A GLOBAL APPROACH FOR GENERAL 0-1 FRACTIONAL-PROGRAMMING

Abstract

Current methods of general 0-1 fractional programming (G-FP) can only find the local optimum. This paper proposes a new method of solving G-FP problems by a mixed 0-1 linear program to obtain a global optimum. Given a mixed 0-1 polynomial term xy where x is a 0-1 variable and 0 < y less-than-or-equal-to 1, we develop a theorem to transfer the xy term into a set of mixed 0-1 linear inequalities. Based on this theorem, a G-FP problem can be solved by a branch-and-bound method to obtain the global solution.