[1] R. G. Bland:
New finite pivoting rules for the simplex method. Math. Oper. Res. 2 (1977), 103-107.
MR 0459599 |
Zbl 0408.90050
[2] P. H. Calamai, J. J. More:
Projected gradient methods for linearly constrained problems. Math. Programming 39 (1987), 93-116.
MR 0909010 |
Zbl 0634.90064
[3] T. F. Coleman:
Large Sparse Numerical Optimization. (Lecture Notes in Computer Science 165.) Springer-Verlag, Berlin-Heidelberg-New York-Tokyo 1984.
MR 0743750 |
Zbl 0536.65047
[4] R. S. Dembo: NLPNET - User's Guide and System Documentation. School of Organiza- tion and Management Working Paper Series B # 70, Yale University, New Haven, CT 1983.
[5] R. S. Dembo:
A primal truncated Newton algorithm with application to large-scale nonlinear network optimization. Math. Programming Study 31 (1987), 43-71.
MR 0903204 |
Zbl 0635.90072
[6] R. S. Dembo S. C. Eisenstat, T. Steihaug:
Inexact Newton methods. SIAM J. Numer. Anal. 79(1982), 400-408.
MR 0650059
[7] R. S. Dembo, J. G. Klincewicz:
Dealing with degeneracy in reduced gradient algorithms. Math. Programming 31 (1985), 357-363.
MR 0783400 |
Zbl 0573.90083
[8] R. S. Dembo, T. Sahi: A convergent active-set strategy for linearly-constrained optimization. School of Organization and Management Working Paper Series B # 80, Yale University 1984.
[9] R. S. Dembo, T. Steihaug:
Truncated-Newton algorithms for large-scale unconstrained optimization. Math. Programming 26 (1983), 190-212.
MR 0700647 |
Zbl 0523.90078
[10] A. Drud:
CONOPT: A GRG code for large sparse dynamic nonlinear optimization problems. Math. Programming 31 (1985), 153-191.
MR 0777289 |
Zbl 0557.90088
[11] L. F. Escudero: An Algorithm for Large-scale Quadratic Programming and its Extensions to the Linearly Constrained Case. IBM Scientic Centre Report SCR-01.81, Madrid 1981.
[12] Y. Fan L. Lasdon, S. Sarkar:
Experiments with successive quadratic programming algorithms. J. Optim. Theory Appl. 56 (1988), 359-383.
MR 0930214
[13] R. Fletcher:
Practical Methods of Optimization. Vol. 2: Constrained Optimization. J. Wiley, New York-Chichester-Brisbane-Toronto 1981.
MR 0633058 |
Zbl 0474.65043
[14] P. E. Gill, W. Murray:
Newton-type methods for unconstrained and linearly constrained optimization. Math. Programming 28 (1974), 311 - 350.
MR 0356503 |
Zbl 0297.90082
[15] P. E. Gill, W. Murray: The Computation of Lagrange Multiplier Estimates for Constrained Minimization. Rep. NAC 77, National Physical Laboratory, England 1976.
[16] W. Hock, K. Schittkowski:
Test Examples for NLP Codes. Springer-Verlag, Berlin-Heidelberg-New York 1981.
MR 0611512
[17] L. Luksan: System UFO. User's Guide-version 1989(in Czech). Res. Rep. V-441, SVT CSAV, Prague, 1989.
[18] H. M. Markowitz:
The elimination form of the inverse and its applications to linear programming. Management Sci. 3 (1957), 225-269.
MR 0112244
[19] B. A. Murtagh:
Advanced Linear Programming: Computation and Practice. McGraw Hill New York 1981.
MR 0609151 |
Zbl 0525.90062
[20] B. A. Murtagh, M. A. Saunders:
Large-scale linearly constrained optimization. Math. Programming 14 (1978), 41 - 72.
MR 0462607 |
Zbl 0383.90074
[21] B. A. Murtagh, M. A. Saunders:
A projected Lagrangian algorithm and its implementation for sparse nonlinear constraints. Math. Programming Study 16 (1982), 84-117.
MR 0650630 |
Zbl 0477.90069
[22] B. A. Murtagh, M. A. Saunders: MINOS 5.1 User's Guide. Tech. Rep. SOL 83-20 R, Dept. Oper. Res., Stanford University, Stanford, CA, 1983, revised 1987.
[23] O. Osterby, Z. Zlatev:
Direct methods for sparse matrices. (Lecture Notes in Computer Science 157.) Springer-Verlag, Berlin -Heidelberg-New York-Tokyo 1983.
MR 0716136 |
Zbl 0516.65011
[24] S. Pissanetzky:
Sparse Matrix Technology. Academic Press, London-Orlando-San Die- go-New York-Austin-Toronto-Montreal-Sydney-Tokyo 1984.
MR 0751237 |
Zbl 0536.65019
[25] J. K. Reid:
On the method of conjugate gradients for the solution of large sparse systems of linear equations. In: Large Sparse Sets of Linear Equations (J. K. Reid, ed.), Academic Press, London 1971, pp. 231 - 254.
MR 0341836
[26] J. K. Reid: Fortran Subroutines for Handling Sparse Linear Programming Bases. Rep. AERE Harwell, R. 8269. Harwell 1976.
[27] J. K. Reid:
A sparsity-exploiting variant of the Bartels-Golub decomposition for linear programming bases. Math. Programming 24 (1982), 55-69.
MR 0667939 |
Zbl 0492.90050
[28] P. S. Ritch:
Discrete optimal control with multiple constraints I: Constraint separation and transformation technique. Automatica 9 (1973), 415-429.
MR 0439328 |
Zbl 0256.49034
[29] M. Tůma: Large and Sparse Quadratic Programming (in Czech). Ph.D. Thesis, SVT CSAV, Prague 1989.
[30] M. Tůma: SPOPT-Program System for the Solution of Large Sparse Problems of Linear and Quadratic Programming (in Czech). Res. Rep. V-391, SVT CSAV, Praha 1989.
[31] Z. Zlatev:
A survey of the advances in the exploitation of the sparsity in the solution of large problems. Internat. Congress on Comp. and Appl. Math., University of Leuven, Belgium 1986.
MR 0920380