Overview
The algorithms studied in chapters 12 and 13 generate converging sequences if the first iterate is close enough to a regular stationary point (see theorems 12.4, 12.5, 12.7, 13.2, and 13.4). Such an iterate is not necessarily at hand, so it is important to have techniques that allow the algorithms to force convergence, even when the starting point is far from a solution. This is known as the globalization of a local algorithm. The term is a little ambiguous, since it may suggest that it has a link with the search of global minimizers of (P EI ). This is not at all the case (for an entry point on global optimization, see [178]).
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© 2003 Springer-Verlag Berlin Heidelberg
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Bonnans, J.F., Gilbert, J.C., Lemaréchal, C., Sagastizábal, C.A. (2003). Exact Penalization. In: Numerical Optimization. Universitext. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-05078-1_14
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DOI: https://doi.org/10.1007/978-3-662-05078-1_14
Publisher Name: Springer, Berlin, Heidelberg
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