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A stable method for solving certain constrained least squares problems. (English) Zbl 0407.90065

MSC:
90C20 Quadratic programming
90C99 Mathematical programming
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[1] J.W. Daniel, W.B. Gragg, L. Kaufman and G.W. Stewart, ”Reorthogonalization and stable algorithms for updating the Gram-Schmidt QR factorization”,Mathematics of Computation 30 (1976) 772–795. · Zbl 0345.65021
[2] G.H. Golub and M.A. Saunders, ”Linear least squares and quadratic programming”, in: J. Abadie, ed.,Integer and nonlinear programming (North-Holland, Amsterdam, 1970) pp. 229–256. · Zbl 0334.90034
[3] C.L. Lawson and R.J. Hanson,Solving least squares problems (Prentice Hall, Englewood Cliffs, NJ, 1974). · Zbl 0860.65028
[4] C. Lemarechal, ”Combining Kelley’s and conjugate gradient methods”, Abstracts, 9th International symposium on mathematical programming, Budapest (1976).
[5] K. Schittkowski and J. Stoer, ”A factorization method for constrained least squares problems with data changes, part 1: theory”, Institut für Angewandte Mathematik und Statistik der Universität Würzburg, Preprint No. 20 (1976). · Zbl 0378.65026
[6] K. Schittkowski and P. Zimmerman, ”A factorization method for constrained least squares problems with data changes, part 2: numerical tests, comparisons and ALGOL codes”, Institut für Angewandte Mathematik und Statistik der Universität Würzburg, Preprint No. 30 (1977).
[7] J. Stoer, ”On the numerical solution of constrained least squares problems”,SIAM Journal on Numerical Analysis 8 (1971) 382–411. · Zbl 0219.90039 · doi:10.1137/0708038
[8] P. Wolfe, ”Finding the nearest point in a polytope”,Mathematical Programming 11 (1976) 128–149. · Zbl 0352.90046 · doi:10.1007/BF01580381
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