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Object-oriented software for quadratic programming
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Source ACM Transactions on Mathematical Software (TOMS) archive
Volume 29 ,  Issue 1  (March 2003) table of contents
Pages: 58 - 81  
Year of Publication: 2003
ISSN:0098-3500
Authors
E. Michael Gertz  University of Wisconsin-Madison, Madison, WI
Stephen J. Wright  University of Wisconsin-Madison, Madison, WI
Publisher
ACM  New York, NY, USA
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ABSTRACT

The object-oriented software package OOQP for solving convex quadratic programming problems (QP) is described. The primal-dual interior point algorithms supplied by OOQP are implemented in a way that is largely independent of the problem structure. Users may exploit problem structure by supplying linear algebra, problem data, and variable classes that are customized to their particular applications. The OOQP distribution contains default implementations that solve several important QP problem types, including general sparse and dense QPs, bound-constrained QPs, and QPs arising from support vector machines and Huber regression. The implementations supplied with the OOQP distribution are based on such well known linear algebra packages as MA27/57, LAPACK, and PETSc. OOQP demonstrates the usefulness of object-oriented design in optimization software development, and establishes standards that can be followed in the design of software packages for other classes of optimization problems. A number of the classes in OOQP may also be reusable directly in other codes.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Balay, S., Gropp, W., Curfman McInnes, L., and Smith, B. 2001. PETSc Users Manual. Mathematics and Computer Science Division, Argonne National Laboratory, 9700 S. Cass Avenue, Argonne, Ill. 60439, Apr.
 
2
Bartlett, R. 1996. An introduction to rSQP++: An object-oriented framework for reduced-space successive quadratic programming. Report, Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Oct.
 
3
Benson, S., Curfman McInnes, L., and Moré, J. J. 2001. TAO users manual. Technical Memorandum ANL/MCS-TM-249, Argonne National Laboratory, Argonne, Ill. Mar.
4
5
 
6
Czyzyk, J., Mehrotra, S., Wagner, M., and Wright, S. J. 1999. PCx: An interior-point code for linear programming. Optimization Methods and Software 11/12, 397--430.
 
7
Demmel, J. W., Gilbert, J. R., and Li, X. S. 1999. SuperLU User's Guide. Available from www. nersc.gov/xiaoye/SuperLU/.
 
8
Deng, H. L., Gouveia, W., and Scales, J. 1994. The CWP object-oriented optimization library. Technical report, Center for Wave Phenomena, Colorado School of Mines, June.
 
9
Dobrian, F., Kumfert, G., and Pothen, A. 2000. The design of sparse direct solvers using object-oriented techniques. In Modern Tools in Scientific Computing A. M. Bruaset, H. P. Langtangen, and E. Quak, Ed., Springer-Verlag, New York.
 
10
Dobrian, F. and Pothen, A. 2000. Oblio: A sparse direct solver library for serial and parallel computations. Tech. Rep. Department of Computer Science, Old Dominion Univ.
 
11
Duff, I. S. and Reid, J. K. 1982. MA27 -- A set of Fortran subroutines for solving sparse symmetric sets of linear equations. Tech. Rep. AERE R10533, AERE Harwell Laboratory, London, England.
 
12
 
13
 
14
Freund, R. and Nachtigal, N. 1991. QMR: A quasi-minimal residual method for non-Hermitian linear systems. Numer. Math. 60, 315--339.
 
15
Gertz, E. M. and Wright, S. J. 2001. OOQP User Guide. Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Ill., September 2001. Available from http://www.cs.wisc.edu/∼swright/OOQP/.
 
16
Gockenbach, M. and Symes, W. 1999. An overview of HCL1.0. ACM Trans. Math. Softw. 25, 191--212.
 
17
 
18
Gondzio, J. and Sarkissian, R. 2002. Parallel interior-point solver for structured linear programs. Tech. Rep. MS-2000-025, Department of Mathematics and Statistics, The University of Edinburgh, Edinburgh, U.K., to appear in Math. Prog.
 
19
HSL: A collection of Fortran codes for large scale scientific computation, 2000. Full details in http://www.numerical.rl.ac.uk/hsl.
 
20
Kelley, C. T. 1995. Iterative Methods for Linear and Nonlinear Equations. Frontiers in Applied Mathematics, No. 16. SIAM Publications, Philadelphia, Pa.
 
21
 
22
 
23
Maros, I. and Mészáros, C. 1999. A repository of convex quadratic programming problems. Optim. Meth. Softw. 11, and 12(Dec.) 671--681.
 
24
Mehrotra, S. 1992. On the implementation of a primal-dual interior point method. SIAM J. Optim. 2, 575--601.
 
25
 
26
 
27
 
28
Wright, S. J. 2001. On reduced convex QP formulations of monotone LCPs. Math. Prog. 90, 459--473.


Collaborative Colleagues:
E. Michael Gertz: colleagues
Stephen J. Wright: colleagues

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