Global optimization for a class of fractional programming problems

Shu Cherng Fang, David Y. Gao, Ruey Lin Sheu, Wenxun Xing

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)


This paper presents a canonical dual approach to minimizing the sum of a quadratic function and the ratio of two quadratic functions, which is a type of non-convex optimization problem subject to an elliptic constraint. We first relax the fractional structure by introducing a family of parametric subproblems. Under proper conditions on the "problem-defining" matrices associated with the three quadratic functions, we show that the canonical dual of each subproblem becomes a one-dimensional concave maximization problem that exhibits no duality gap. Since the infimum of the optima of the parameterized subproblems leads to a solution to the original problem, we then derive some optimality conditions and existence conditions for finding a global minimizer of the original problem. Some numerical results using the quasi-Newton and line search methods are presented to illustrate our approach.

Original languageEnglish
Pages (from-to)337-353
Number of pages17
JournalJournal of Global Optimization
Issue number3
Publication statusPublished - 2009 Nov

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Management Science and Operations Research
  • Control and Optimization
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Global optimization for a class of fractional programming problems'. Together they form a unique fingerprint.

Cite this