Abstract
We consider a parallel variant of the Newton-Raphson method for unconstrained optimization, which uses as many finite differences of gradients as possible to approximate rows and columns of the inverse Hessian matrix. The method is based on the Gauss-Seidel type of updating for quasi-Newton methods originally proposed by Straeter (1973). It incorporates the finite-difference approximations via the Barnes-Rosen corrections analysed by Van Laarhoven (1985). At the end of the paper we discuss the potential of the method for on-line, real-time optimization.
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© 1990 Springer-Verlag Berlin Heidelberg
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Lootsma, F.A. (1990). An Asynchronous Newton-Raphson Method. In: Kowalik, J.S. (eds) Supercomputing. NATO ASI Series, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-75771-6_25
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DOI: https://doi.org/10.1007/978-3-642-75771-6_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-75773-0
Online ISBN: 978-3-642-75771-6
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