Download PDF by Almerico Murli, Gerardo Toraldo: Computational Issues in High Performance Software for

By Almerico Murli, Gerardo Toraldo

ISBN-10: 0585267782

ISBN-13: 9780585267784

ISBN-10: 0792398629

ISBN-13: 9780792398622

A different factor of , v.7, no.1 (1997), containing papers from a June 1995 convention held in Capri, Italy. Papers evaluation contemporary advancements regarding software program for nonlinear optimization, reflecting assorted views on well-established algorithms for nonlinear difficulties, quickly algorithms for large-scale optimization difficulties, direct tools for answer of sparse linear algebra difficulties, and LCP solvers.

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In order to accelerate the convergence of the method, it is normal to try to bias the computed step towards the Newton direction. The convergence analysis given by Conn et al. [5] for the Outer-iteration Algorithm indicates that it is desirable to construct improvements beyond the Cauchy point only in the subspace of variables which are free from their bounds at the Cauchy point. In particular, with such a restriction and with a suitable non-degeneracy assumption, it is then shown that the set of variables which are free from their bounds at the solution is determined after a finite number of iterations.

Moreover it is easy to show that that AS4, AS5 and AS7 guarantee AS9 provided that pmjn is sufficiently small and sufficient second-order optimality conditions (see Fiacco and McCormick [ 121, Theorem 4) hold at x* (see Wright [ 171, Theorem 8, for the essence of a proof of this in our case). Although we shall merely assume that AS9 holds in this paper, it is of course possible to try to encourage this eventuality. We might, for instance, insist that Step 4 of the Outer-iteration Algorithm is executed rather than Step 3 so long as the matrix H(',') is not positive definite.

L. Toint. On large scale nonlinear least squares calculations. SIAM J. Sci. Statist. , 8:41&435, 1987. 21. Ph. L. Toint and D. Tuyttens. On large-scale nonlinear network optimization. Math. Programming, 48: 125159, 1990. 22. Ph. L. Toint and D. Tuyttens. LSNNO: A Fortran subroutine for solving large-scale nonlinear network optimization problems. ACM Trans. Math. Sojhvare, 18:308-328, 1992. Computational Optimization and Applications, 7,41-69 (1997) @ 1997 Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.

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Computational Issues in High Performance Software for Nonlinear Optimization by Almerico Murli, Gerardo Toraldo


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