A. R. Conn, Constrained
optimization using a nondifferentiable penalty function, SIAM J.
Numer. Anal., 10 (1973), pp. 760-779.
G. B. Dantzig, Linear
Programming and Extensions, Princeton University Press, Princeton,
New Jersey, 1963.
S.K. Eldersveld, Large-scale
sequential quadratic programming algorithms, PhD thesis, Department
of Operations Research, Stanford University, Stanford, CA, 1991.
R. Fletcher, An
l1
penalty method for nonlinear constraints,
in Numerical Optimization 1984, P. T. Boggs, R. H. Bryd, and R. B. Schnabel,
eds., Philadelphia, 1985, SIAM, pp. 26-44.
R. Fourer, Solving
staircase linear programs by the simplex method. 1: Inversion,
Math. Prog., 23 (1982), pp.274-313.
P. E. Gill, W. Murray, and M. A.
Saunders, SNOPT: An SQP algorithm for
large-scale constrained optimization, Numerical Analysis Report
97-2, Department of Mathematics, University of California, San Diego,
La Jolla, CA, 1997.
P. E. Gill, W. Murray, M. A. Saunders,
and M. H. Wright, User's guide for NPSOL
(Version 4.0): a Fortran package for nonlinear programming, Report
SOL 86-2, Department of Operations Research, Stanford University, Stanford,
CA, 1986.
Maintaining
LU factors of a general sparse matrix, Linear Algebra and its Applications,
88/89 (1987), pp. 239-270.
A
practical anti-cycling procedure for linearly constrained optimization,
Math. Prog., 45 (1989), pp. 437-474.
Some
theoretical properties of an augmented Lagrangian merit function, in Advances
in Optimization and Parallel Computing, P. M. Pardalos, ed., North
Holland, 1992, pp. 101-128.
B. A. Murtagh and M. A. Saunders,
Large-scale linearly constrained optimization,
Math. Prog., 14 (1978), pp. 41-72.
A
projected Lagrangian algorithm and its implementation for sparse nonlinear
constraints, Math. Prog. Study, 16
(1982), pp. 84-117.
MINOS
5.4 User's Guide, Report SOL, 83-20R, Department of Operations
Research, Stanford University, Stanford, CA, Revised 1995.