Canonical dual transformation method and generalized triality theory in nonsmooth global optimization
| Venue: | Journal of Global Optimization |
| Citations: | 15 - 9 self |
BibTeX
@ARTICLE{Gao_canonicaldual,
author = {David Yang Gao},
title = {Canonical dual transformation method and generalized triality theory in nonsmooth global optimization},
journal = {Journal of Global Optimization},
year = {},
pages = {127--160}
}
Years of Citing Articles
OpenURL
Abstract
Abstract. This paper presents, within a unified framework, a potentially powerful canonical dual transformation method and associated generalized duality theory in nonsmooth global optimization. It is shown that by the use of this method, many nonsmooth/nonconvex constrained primal problems in R n can be reformulated into certain smooth/convex unconstrained dual problems in R m with m � n and without duality gap, and some NP-hard concave minimization problems can be transformed into unconstrained convex minimization dual problems. The extended Lagrange duality principles proposed recently in finite deformation theory are generalized suitable for solving a large class of nonconvex and nonsmooth problems. The very interesting generalized triality theory can be used to establish nice theoretical results and to develop efficient alternative algorithms for robust computations.







