Skip to main content
Log in

Updating conjugate directions by the BFGS formula

  • Published:
Mathematical Programming Submit manuscript

Abstract

Many iterative algorithms for optimization calculations form positive definite second derivative approximations,B say, automatically, butB is not stored explicitly because of the need to solve equations of the formBd--g. We consider working with matricesZ, whose columns satisfy the conjugacy conditionsZ 1 BZ=1. Particular attention is given to updatingZ in a way that corresponds to revisingB by the BFGS formula. A procedure is proposed that seems to be much more stable than the direct use of a product formula [1]. An extension to this procedure provides some automatic rescaling of the columns ofZ, which avoids some inefficiencies due to a poor choice of the initial second derivative approximation. Our work is also relevant to active set methods for linear inequality constraints, to updating the Cholesky factorization ofB, and to explaining some properties of the BFGS algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. K.W. Brodlie, A.R. Gourlay and J. Greenstadt, “Rank-one and rank-two corrections to positive definite matrices expressed in product form”,Journal of the Institute of Mathematics and its Applications 11 (1973) 73–82.

    MATH  MathSciNet  Google Scholar 

  2. W.C. Davidon, “Optimally conditioned optimization algorithms without line searches”,Mathematical Programming 9 (1975) 1–30.

    Article  MATH  MathSciNet  Google Scholar 

  3. R. Fletcher,Practical Methods of Optimization, Vol. 1: Unconstrained Optimization (John Wiley & Sons, Chichester, 1980).

    MATH  Google Scholar 

  4. R. Fletcher and M.J.D. Powell, “On the modification ofLDL T factorizations”,Mathematics of Computation 28 (1974) 1067–1087.

    Article  MATH  MathSciNet  Google Scholar 

  5. W.M. Gentleman, “Least squares computations by Givens transformations without square roots,”Journal of the Institute of Mathematics and its Applications 12 (1973) 329–336.

    Article  MATH  MathSciNet  Google Scholar 

  6. P.E. Gill and W. Murray, “Quasi-Newton methods for unconstrained optimization”,Journal of the Institute of Mathematics and its Applications 9 (1972) 91–108.

    MATH  MathSciNet  Google Scholar 

  7. D. Goldfarb, “Factorized variable metric methods for unconstrained optimization”,Mathematics of Computation 30 (1976) 796–811.

    Article  MATH  MathSciNet  Google Scholar 

  8. D. Goldfarb and A. Idnani, “A numerically stable dual method for solving strictly convex quadratic programs”,Mathematical Programming 27 (1983) 1–33.

    MATH  MathSciNet  Google Scholar 

  9. S-P. Han, “Optimization by updated conjugated subspaces,” in: D.F. Griffiths and G.A. Watson, eds.,Numerical Analysis: Pitman Research Notes in Mathematics Series 140 (Longman Scientific & Technical, Burnt Mill, England) pp. 82–97.

  10. W. Murray, “An algorithm for finding a local minimum of an indefinite quadratic program,” Report NAC 1, National Physical Laboratory, Teddington (1971).

    Google Scholar 

  11. M.J.D. Powell, “On the quadratic programming algorithm of Goldfarb and Idnani,”Mathematical Programming Study 25 (1985) 46–61.

    MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

Dedicated to Martin Beale, whose achievements, advice and encouragement were of great value to my research, especially in the field of conjugate direction methods.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Powell, M.J.D. Updating conjugate directions by the BFGS formula. Mathematical Programming 38, 29–46 (1987). https://doi.org/10.1007/BF02591850

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02591850

Key words

Navigation