- Title
- On modeling and global solutions for d.c. optimization problems by canonical duality theory
- Creator
- Jin, Zhong; Gao, David
- Date
- 2017
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/104304
- Identifier
- vital:11036
- Identifier
-
https://doi.org/10.1016/j.amc.2016.10.010
- Identifier
- ISSN:00963003
- Abstract
- This paper presents a canonical d.c. (difference of canonical and convex functions) programming problem, which can be used to model general global optimization problems in complex systems. It shows that by using the canonical duality theory, a large class of nonconvex minimization problems can be equivalently converted to a unified concave maximization problem over a convex domain, which can be solved easily under certain conditions. Additionally, a detailed proof for triality theory is provided, which can be used to identify local extremal solutions. Applications are illustrated and open problems are presented.
- Publisher
- Elsevier Inc.
- Relation
- Applied Mathematics and Computation Vol. 296, no. (2017), p. 168-181
- Rights
- Copyright © 2016 Elsevier Inc.
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0102 Applied Mathematics; 0103 Numerical and Computational Mathematics; Canonical duality theory; D.C. programming; Global optimization; Mathematical modeling
- Full Text
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