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Your search keyword '"Chun-Feng, Wang"' showing total 2 results
Start Over Author "Chun-Feng, Wang" Topic branch and bound Topic fractional programming
2 results on '"Chun-Feng, Wang"'

1. A New Branch and Reduce Approach for Solving Generalized Linear Fractional Programming.

Author

Yong-Hong Zhang and Chun-Feng Wang

Subjects
*FRACTIONAL programming, *MATHEMATICAL sequences, *ALGORITHMS, *STOCHASTIC convergence, *PROBLEM solving
Abstract

In this paper, for solving generalized linear fractional programming (GLFP), a new branch-and-reduce approach is presented. Firstly, an equivalent problem (EP) of GLFP is given; then, a new linear relaxation technique is proposed; finally, the problem EP is reduced to a sequence of linear programming problems by using the new linear relaxation technique. Meanwhile, to improve the convergence speed of our algorithm, two reducing techniques are presented. The proposed algorithm is proved to be convergent, and some experiments are provided to show its feasibility and efficiency. [ABSTRACT FROM AUTHOR]

Published
2017

2. Global optimization for sum of generalized fractional functions

Author

Peiping Shen and Chun-Feng Wang

Subjects
Mathematical optimization, Linear programming, Linear relaxation, Applied Mathematics, Generalized fractional programming, Nonlinear programming, Linear-fractional programming, Computational Mathematics, Fractional programming, Linearization, Global optimization, Branch and bound, Criss-cross algorithm, Geometric programming, Mathematics
Abstract

This paper considers the solution of generalized fractional programming (GFP) problem which contains various variants such as a sum or product of a finite number of ratios of linear functions, polynomial fractional programming, generalized geometric programming, etc. over a polytope. For such problems, we present an efficient unified method. In this method, by utilizing a transformation and a two-part linearization method, a sequence of linear programming relaxations of the initial nonconvex programming problem are derived which are embedded in a branch-and-bound algorithm. Numerical results are given to show the feasibility and effectiveness of the proposed algorithm.

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