- Title
- An update rule and a convergence result for a penalty function method
- Creator
- Burachik, Regina; Kaya, Yalcin
- Date
- 2007
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/54291
- Identifier
- vital:153
- Identifier
- ISSN:1547-5816
- Identifier
-
https://doi.org/10.3934/jimo.2007.3.381
- Abstract
- We use a primal-dual scheme to devise a new update rule for a penalty function method applicable to general optimization problems, including nonsmooth and nonconvex ones. The update rule we introduce uses dual information in a simple way. Numerical test problems show that our update rule has certain advantages over the classical one. We study the relationship between exact penalty parameters and dual solutions. Under the differentiability of the dual function at the least exact penalty parameter, we establish convergence of the minimizers of the sequential penalty functions to a solution of the original problem. Numerical experiments are then used to illustrate some of the theoretical results.; C1
- Publisher
- Springfield, MO, USA AIMS American Institute of Mathematical Sciences
- Relation
- Journal of Industrial & Management Optimization Vol. 3, no. 2 (2007), p. 381-398
- Rights
- Open Access
- Rights
- Copyright American Institute of Mathematical Sciences
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0103 Numerical and Computational Mathematics; Penalty function method; Penalty parameter update; Least exact penalty parameter; Duality; Nonsmooth optimization; Nonconvex optimization
- Full Text
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