1. Linear decomposition approach for a class of nonconvex programming problems
- Author
-
Peiping Shen and Chun-Feng Wang
- Subjects
Mathematical optimization ,Linear programming ,Computational complexity theory ,0211 other engineering and technologies ,010103 numerical & computational mathematics ,02 engineering and technology ,01 natural sciences ,nonconvex programming ,linear decomposition approach ,Discrete Mathematics and Combinatorics ,0101 mathematics ,Global optimization ,approximation algorithm ,Mathematics ,computational complexity ,021103 operations research ,Series (mathematics) ,lcsh:Mathematics ,Research ,global optimization ,Applied Mathematics ,90C30 ,Approximation algorithm ,90C33 ,lcsh:QA1-939 ,Grid ,90C15 ,Linear-fractional programming ,Criss-cross algorithm ,Analysis - Abstract
This paper presents a linear decomposition approach for a class of nonconvex programming problems by dividing the input space into polynomially many grids. It shows that under certain assumptions the original problem can be transformed and decomposed into a polynomial number of equivalent linear programming subproblems. Based on solving a series of liner programming subproblems corresponding to those grid points we can obtain the near-optimal solution of the original problem. Compared to existing results in the literature, the proposed algorithm does not require the assumptions of quasi-concavity and differentiability of the objective function, and it differs significantly giving an interesting approach to solving the problem with a reduced running time.
- Published
- 2017