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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Journal of optimization theory and applications 106 (2000), S. 551-568 
    ISSN: 1573-2878
    Keywords: nonsmooth optimization ; inexact Newton methods ; generalized Newton methods ; global convergence ; superlinear rate
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Motivated by the method of Martinez and Qi (Ref. 1), we propose in this paper a globally convergent inexact generalized Newton method to solve unconstrained optimization problems in which the objective functions have Lipschitz continuous gradient functions, but are not twice differentiable. This method is implementable, globally convergent, and produces monotonically decreasing function values. We prove that the method has locally superlinear convergence or even quadratic convergence rate under some mild conditions, which do not assume the convexity of the functions.
    Type of Medium: Electronic Resource
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Journal of optimization theory and applications 67 (1990), S. 369-393 
    ISSN: 1573-2878
    Keywords: Two-sided projected Hessians ; trust regions ; differentiable penalty functions ; global convergence ; two-step Q-superlinear rate ; constrained optimization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In Ref. 1, Nocedal and Overton proposed a two-sided projected Hessian updating technique for equality constrained optimization problems. Although local two-step Q-superlinear rate was proved, its global convergence is not assured. In this paper, we suggest a trust-region-type, two-sided, projected quasi-Newton method, which preserves the local two-step superlinear convergence of the original algorithm and also ensures global convergence. The subproblem that we propose is as simple as the one often used when solving unconstrained optimization problems by trust-region strategies and therefore is easy to implement.
    Type of Medium: Electronic Resource
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