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Large-Scale PDE-Constrained Optimization pp 316–330Cite as

rSQP++ : An Object-Oriented Framework for Successive Quadratic Programming

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Part of the book series: Lecture Notes in Computational Science and Engineering ((LNCSE,volume 30))

Abstract

An Object-Oriented (OO) framework called rSQP++ is currently being developed for Successive Quadratic Programming (SQP). It is designed to support many different SQP algorithms and to allow for extern al configur at ion of application-specific linear algebra objects such as matrices and linear solvers. In addition, it is possible for a client to modify the SQP algorithms to meet other specialized needs without having to touch any of th e source code within the rSQP++ framework or even having to recompile existing SQP algorithms. Much of this is accomplished through a set of carefully constructed interfaces to various linear algebra objects such as matrices and linear solvers. The initial development of rSQP++ was done in a serial environment and therefore issues related to the use of massively parallel iterative solvers used in PDE-constrained optimization have not yet been addressed. In order to more effectively support parallelism, rSQP++ needs the addition and integration of an abstract vector interface to allow more flexibility in vector implementations. Encapsulating vectors away from algorithmic code would allow fully parallel linear algebra, but could also greatly restrict the kinds of operations that need to be performed. The difficulty in developing an abstract vector interface and a proposed design for a remedy are discussed.

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Author information

Authors and Affiliations

  1. Department of Chemical Engineering, Carnegie Mellon University, USA

    Roscoe A. Bartlett & Lorenz T. Biegler

Authors
  1. Roscoe A. Bartlett
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  2. Lorenz T. Biegler
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Editor information

Editors and Affiliations

  1. Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    Lorenz T. Biegler

  2. Department of Computational and Applied Mathematics, Rice University, 6100 S. Main Street — MS134, Houston, TX, 77005, USA

    Matthias Heinkenschloss

  3. Department of Biomedical Engineering and Civil & Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    Omar Ghattas

  4. Optimization & Uncertainty Estimation Dept., Sandia National Laboratories — MS 0847, P.O. Box 5800, Albuquerque, NM, 87185, USA

    Bart van Bloemen Waanders

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© 2003 Springer-Verlag Berlin Heidelberg

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Bartlett, R.A., Biegler, L.T. (2003). rSQP++ : An Object-Oriented Framework for Successive Quadratic Programming. In: Biegler, L.T., Heinkenschloss, M., Ghattas, O., van Bloemen Waanders, B. (eds) Large-Scale PDE-Constrained Optimization. Lecture Notes in Computational Science and Engineering, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55508-4_19

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  • DOI: https://doi.org/10.1007/978-3-642-55508-4_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-05045-2

  • Online ISBN: 978-3-642-55508-4

  • eBook Packages: Springer Book Archive

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