Global optimization by canonical dual function

Authors:
Jinghao Zhu;Jiani Zhou;David Gao
Affiliations:
Department of Applied Mathematics, Tongji University, Shanghai, China;Department of Mathematics, Tongji University, Shanghai, China;Department of Mathematics, Virginia Tech, Blacksburg, USA
Venue:
Journal of Computational and Applied Mathematics
Year:
2010

Citing 4
Cited 1

On affine scaling algorithms for nonconvex quadratic programming

Mathematical Programming: Series A and B
Analytic solutions and triality theory for nonconvex and nonsmooth variational problems with applications

Nonlinear Analysis: Theory, Methods & Applications
Canonical Duality Theory and Solutions to Constrained Nonconvex Quadratic Programming

Journal of Global Optimization
A study on concave optimization via canonical dual function

Journal of Computational and Applied Mathematics

Global optimization over a box via canonical dual function

Journal of Computational and Applied Mathematics

Quantified Score

Hi-index	7.29

Visualization

Abstract

In this paper, the canonical dual function (Gao, 2004 [4]) is used to solve a global optimization. We find global minimizers by backward differential flows. The backward flow is created by the local solution to the initial value problem of an ordinary differential equation. Some examples and applications are presented.