Generalized primal-relaxed dual approach for global optimization

Liu, Steve Wenbin and Floudas, Christodoulos A. (1996) Generalized primal-relaxed dual approach for global optimization. Journal of Optimization Theory and Applications, 90 (2). pp. 417-434. ISSN 0022-3239. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Official URL
http://dx.doi.org/10.1007/BF02190006

Abstract

A generalized primal-relaxed dual algorithm for global optimization is proposed and its convergence is proved. The (GOP) algorithm of Floudas and Visweswaran (Refs. 1-2) is shown to be a special case of this general algorithm. Within the proposed framework, the algorithm of Floudas and Visweswaran (Refs. 1-2) is further extended to the nonsmooth case. A penalty implementation of the extended (GOP) algorithm is studied to improve its efficiency.

Item Type: Article
Uncontrolled keywords: global optimization; primal-relaxed dual approach; penalty methods; nonsmooth optimization
Subjects: H Social Sciences > HA Statistics > HA33 Management Science
Q Science > QA Mathematics (inc Computing science)
Q Science > Operations Research - Theory
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science
Faculties > Social Sciences > Kent Business School
Faculties > Social Sciences > Kent Business School > Management Science
Central Services > Templeman Library
Depositing User: F.D. Zabet
Date Deposited: 29 Jun 2009 11:23
Last Modified: 04 Jul 2014 13:31
Resource URI: https://kar.kent.ac.uk/id/eprint/18647 (The current URI for this page, for reference purposes)
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