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On the use of directions of negative curvature in a modified newton method

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Abstract

We present a modified Newton method for the unconstrained minimization problem. The modification occurs in non-convex regions where the information contained in the negative eigenvalues of the Hessian is taken into account by performing a line search along a path which is initially tangent to a direction of negative curvature. We give termination criteria for the line search and prove that the resulting iterates are guaranteed to converge, under reasonable conditions, to a critical point at which the Hessian is positive semidefinite. We also show how the Bunch and Parlett decomposition of a symmetric indefinite matrix can be used to give entirely adequate directions of negative curvature.

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References

  1. J.O. Aasen, “On the reduction of a symmetric matrix to tridiagonal form”,BIT 11 (1971) 233–242.

    Google Scholar 

  2. L. Armijo, “Minimization of functions having Lipschitz continuous first partial derivatives”,Pacific Journal of Mathematics 16 (1966) 1–3.

    Google Scholar 

  3. J.R. Bunch and B.N. Parlett, “Direct methods for solving symmetric indefinite systems of linear equations”,SIAM Journal on Numerical Analysis 8 (1971) 639–655.

    Google Scholar 

  4. J.R. Bunch and L. Kaufman, “Some stable methods for calculating inertia and solving symmetric linear equations”,Mathematics of Computation 31 (1977) 163–179.

    Google Scholar 

  5. A.V. Fiacco, and G.P. McCormick,Nonlinear programming: sequential unconstrained minimization techniques (Wiley, New York, 1968).

    Google Scholar 

  6. R. Fletcher and T.L. Freeman, “A modified Newton method for minimization”,Journal of Optimization Theory and Applications 23 (1977) 357–372.

    Google Scholar 

  7. P.E. Gill and W. Murray, “Newton type methods for unconstrained and linearly constrained optimization”,Mathematical Programming 7 (1974) 311–350.

    Google Scholar 

  8. P.E. Gill and W. Murray, “Safeguarded steplength algorithms for optimization using descent methods”, National Physical Laboratory, Rep. NAC37 (1974).

  9. G. McCormick, “A modification of Armijo's step-size rule for negative curvature”,Mathematical Programming 13 (1977) 111–115.

    Google Scholar 

  10. H. Mukai and E. Polak, “A second order method for unconstrained optimization”,Journal of Optimization Theory and Applications (1978). to appear.

  11. J.M. Ortega, and W.C. Rheinboldt,Iterative solution of nonlinear equations in several variables (Academic Press, New York, 1970).

    Google Scholar 

  12. D.C. Sorensen, “Updating the symmetric indefinite factorization with applications in a modified Newton's method”, Ph.D. thesis, University of California at San Diego, Argonne National Laboratory Rep. ANL-77-49, (1977).

  13. P. Wolfe, “Convergence conditions for ascent methods II: Some corrections”,SIAM Review 13 (1971) 185–188.

    Google Scholar 

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Work performed under the auspices of the U.S. Department of Energy.

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Moré, J.J., Sorensen, D.C. On the use of directions of negative curvature in a modified newton method. Mathematical Programming 16, 1–20 (1979). https://doi.org/10.1007/BF01582091

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  • DOI: https://doi.org/10.1007/BF01582091

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