Linearly constrained linear least squares problems and convex quadratic programmming
LSSOL is designed to solve a class of linear and quadratic programming problems of the following general form:
Equations are missing here
LSSOL uses a two-phase, active-set method related to the method used in the package QPOPT. Two special features of LSSOL are its exploitation of convexity and treatment of singularity. LSSOL treats all matrices as dense and is not intended for sparse problems.
The LSSOL package contains approximately 15,000 lines of Fortran, of which about 75% are comments. The source code and example program for LSSOL are distributed on a floppy disk. The code is also available via Internet using ftp. A Matlab interface for LSSOL is also available.
LSSOL includes calls to both Level-1 (vector) and Level-2 (matrix-vector) Basic Linear Algebra Subroutines (BLAS). They may be replaced by versions of the BLAS routines that have been tuned to a particular machine.
LSSOL is written in ANSI Fortran 77 and should run without alteration on any machine with a Fortran 77 compiler. The code was developed on a DECstation 3100 using the MIPS f77 compiler and has been installed on most types of PC, workstation, and mainframe.
LSSOL is distributed on floppy disk. Fortran 77 source code is provided, along with test problems and makefiles for Unix, VMS and DOS systems.
One-time license fees for individual use are $200 (academic or non-profit) and $2000 (commercial, in-house). Department, Site and World licenses are also available.
Contact:
Stanford Business Software, Inc. 2672 Bayshore Parkway, Suite 304 Mountain View, CA 94043 Phone: (415) 962-8719 Fax: (415) 962-1869
P.E. Gill, S.J. Hammarling, W.Murray, M.A. Saunders, and M.H. Wright, User's Guide for LSSOL (Version 1.0): A Fortran package for constrained linear least-squares and convex quadratic programming, SOL86-1, 1986.
The NAG Fortran Library, Numerical Algorithms Group Limited, Wilkinson House, Jordan Hill Road, Oxford, England.
J. Stoer, On the numerical solution of constrained least-squares problems, SIAM J. Numer. Anal. 8 (1971), pp.~382--411.
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