A Novel Approach for Solving Quadratic Fractional Programming Problems

Abstract

In this paper, quadratic fractional programming (QFP) problems involving a factorized or non-factorized objective function and subject to homogenous or non-homogenous constraints are considered. Our proposed approach depends on a computational method that converts the QFP problem into a linear programming (LP) problem by using a Taylor series to solve the problem algebraically. This approach, based on the solution of LP problems, can be applied to various types of nonlinear fractional programming problems containing nonlinear constraint(s), and minimizes the total execution time on iterative operations. To illustrate the solution process, two examples are presented and the proposed approach is compared with other two existing methods for solving QFP problems.