Restart procedures for the conjugate gradient method

M. J. D. Powell

doi:10.1007/bf01593790

journal article Dec 01, 1977

Restart procedures for the conjugate gradient method

M. J. D. Powell

Mathematical Programming Vol. 12 No. 1 pp. 241-254 · Springer Science and Business Media LLC

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References

10

[1]

E.M.L. Beale, “A derivation of conjugate gradients”, in: F.A. Lootsma, ed.,Numerical methods for nonlinear optimization (Academic Press, London, 1972) pp. 39–43.

[2]

H.P. Crowder and P. Wolfe, “Linear convergence of the conjugate gradient method”,IBM Journal of Research and Development 16 (1972) 431–433. 10.1147/rd.164.0431

[3]

R. Fletcher, “A Fortran subroutine for minimization by the method of conjugate gradients”, Report R-7073, A.E.R.E., Harwell, 1972.

[4]

R. Fletcher and M.J.D. Powell, “A rapidly convergent descent method for minimization”,Computer Journal 6 (1963) 163–168. 10.1093/comjnl/6.2.163

[5]

R. Fletcher and C.M. Reeves, “Function minimization by conjugate gradients”,Computer Journal 7 (1964) 149–154. 10.1093/comjnl/7.2.149

[6]

D.G. Luenberger,Introduction to linear and nonlinear programming (Addison-Wesley, New York, 1973).

[7]

M.F. McGuire and P. Wolfe, “Evaluating a restart procedure for conjugate gradients”, Report RC-4382, IBM Research Center, Yorktown Heights, 1973.

[8]

E. Polak,Computational methods in optimization: a unified approach (Academic Press, London, 1971).

[9]

M.J.D. Powell, “Some convergence properties of the conjugate gradient method”,Mathematical Programming 11 (1976) 42–49. 10.1007/bf01580369

[10]

G. Zoutendijk, “Nonlinear programming, computational methods”, in: J. Adabie, ed.,Integer and nonlinear programming (North-Holland, Amsterdam, 1970) pp. 37–86.

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Details

Published: Dec 01, 1977
Vol/Issue: 12(1)
Pages: 241-254
License: View

Authors

M

M. J. D. Powell

Cite This Article

M. J. D. Powell (1977). Restart procedures for the conjugate gradient method. Mathematical Programming, 12(1), 241-254. https://doi.org/10.1007/bf01593790

Restart procedures for the conjugate gradient method

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