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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Booch, G., J. Rumbaugh, and I. Jacobson. “The Unified Modeling Language User Guide.” Addison-Wesley, New York (1999)
Bartlett, R. “An Introduction to rSQP++: An Object-Oriented Framework for Reduced Space Successive Quadratic Programming” Technical Report, Department of Chemical Engineering, Carniege Mellon University (2000)
Bartlett, R. “New Object-Oriented Approaches to SQP for Large-Scale Process Optimization” Parallel and Large-Scale Computing: algorithms and Applications, AICHE Annual Meeting, Los Angeles (2000)
Biegler, L., A. Cervantes and A. Waechter. “Advances in Simultaineous Strategies for Dynamic Optimization.” CAPD Technical Report B-01-01, Department of Chemical Engineering, Carniege Mellon University (2001)
Nocedal, J. and M. Overton. “Projected Hessian Updating Algorithms for Nonlinear Constrained Optimization”. SIAM J. Nutner. Anal., Philadelphia, 22, 821 (1985)
Nocedal, J. and Stephen Wright. “umerical Optimization”. Springer, New York, (1999)
Rumbaugh, J. et, al. “bject-Oriented Modeling and Design.” Prentice Hall, Englewood Cliffs, New Jersey (1991)
Schmid, C. and L.T. Biegler. “Accelerat ion of Reduced Hessian Methods for Large-Scale Nonlinear Programming.” Camp. Chem. Eng. 17, 451 (1993)
Schmid, C. and L.T. Biegler. “Quadratic Programming Methods for Reduced Hessian SQP.” Camp. Chem. Eng. 18, 817 (1994)
van Bloemen Waanders, B., A. Salinger, R. Pawlowski, L. Biegler, R. Bartlett “Simult aneous Analysis and Design Optimization of Massively Parallel Simulation Codes using an Obj ect Oriented Framework.” Tenth SIAM Conference on Parallel Processing for Scientific Computing (SIAG/SC) (PPOl) March (2001)
Womble, D.E, S.S. Dosanjh, B. Hendrickson, M.A. Heroux, S.J. Plimpton, J.L. Tomkins and D.S. Greenberg. “Massively Parallel Computing: A Sandia Perspective.” Parallel Computing, 25, 1853–1876 (1999)
Wright, S. “Optimization Software Packages.” ANL/MCS-P8xx:-0899, Mathematics and Computer Science Division, Argonne National Laboratory (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
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