Solving a class of generalized fractional programming problems using the feasibility of linear programs

30Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

This article presents a new approximation algorithm for globally solving a class of generalized fractional programming problems (P) whose objective functions are defined as an appropriate composition of ratios of affine functions. To solve this problem, the algorithm solves an equivalent optimization problem (Q) via an exploration of a suitably defined nonuniform grid. The main work of the algorithm involves checking the feasibility of linear programs associated with the interesting grid points. It is proved that the proposed algorithm is a fully polynomial time approximation scheme as the ratio terms are fixed in the objective function to problem (P), based on the computational complexity result. In contrast to existing results in literature, the algorithm does not require the assumptions on quasi-concavity or low-rank of the objective function to problem (P). Numerical results are given to illustrate the feasibility and effectiveness of the proposed algorithm.

Cite

CITATION STYLE

APA

Shen, P., Zhang, T., & Wang, C. (2017). Solving a class of generalized fractional programming problems using the feasibility of linear programs. Journal of Inequalities and Applications, 2017(1). https://doi.org/10.1186/s13660-017-1420-1

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free