Large-Scale Dynamic Optimization Using the Directional Second-Order Adjoint Method

Truncated-Newton methods provide an effective way to solve large-scale optimization problems by achieving savings in computation and storage. For dynamic optimization, the Hessian−vector products required by these methods can be evaluated accurately at a computational cost which is usually insensiti...

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Bibliographic Details
Published in:Industrial & engineering chemistry research 2005-03, Vol.44 (6), p.1804-1811
Main Authors: Özyurt, Derya B, Barton, Paul I
Format: Article
Language:English
Subjects:
Applied sciences
Chemical engineering
Exact sciences and technology
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Summary:Truncated-Newton methods provide an effective way to solve large-scale optimization problems by achieving savings in computation and storage. For dynamic optimization, the Hessian−vector products required by these methods can be evaluated accurately at a computational cost which is usually insensitive to the number of optimization variables using a novel directional second-order adjoint (dSOA) method. The case studies presented in this paper demonstrate that a “dSOA-powered” truncated-Newton method is a promising candidate for the solution of large-scale dynamic optimization problems.
ISSN:0888-5885
1520-5045
DOI:10.1021/ie0494061