A heuristic algorithm for nonlinear programming |
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| Authors: | R. Fontecilla |
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| Affiliation: | (1) Department of Computer Science, Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland |
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| Abstract: | In this paper, a heuristic algorithm for nonlinear programming is presented. The algorithm uses two search directions, and the Hessian of the Lagrangian function is approximated with the BFGS secant update. We show that the sequence of iterates convergeq-superlinearly if the sequence of approximating matrices satisfies a particular condition. Numerical results are presented. |
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| Keywords: | Nonlinear programming constrained minimization quasi-Newton methods secant methods |
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