A global optimization algorithm for linear fractional programming

doi:10.1016/j.amc.2008.06.045

2008-10-01

PRE

Chunfeng Wang *

申

申培萍 (Peiping Shen)

DOI：10.1016/j.amc.2008.06.045

原文链接

原文求助

摘要

En 中文

In this paper, we present an efficient branch and bound method for general linear fractional problem (GFP). First, by using a transformation technique, an equivalent problem (EP) of GFP is derived, then by exploiting structure of EP, a linear relaxation programming (LRP) of EP is obtained. To implement the algorithm, the main computation involve solving a sequence of linear programming problem, which can be solved efficiently. The proposed algorithm is convergent to the global maximum through the successive refinement of the solutions of a series of linear programming problems. Numerical experiments are reported to show the feasibility of our algorithm. (C) 2008 Elsevier Inc. All rights reserved.

Keyword:

global optimization

linear relaxation

branch and bound

fractional programming

sum-of-ratios