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|Type:||Artigo de periódico|
|Title:||Separable Cubic Modeling And A Trust-region Strategy For Unconstrained Minimization With Impact In Global Optimization|
|Abstract:||A separable cubic model, for smooth unconstrained minimization, is proposed and evaluated. The cubic model uses some novel secant-type choices for the parameters in the cubic terms. A suitable hard-case-free trust-region strategy that takes advantage of the separable cubic modeling is also presented. For the convergence analysis of our specialized trust region strategy we present as a general framework a model (Formula presented.)-order trust region algorithm with variable metric and we prove its convergence to (Formula presented.)-stationary points. Some preliminary numerical examples are also presented to illustrate the tendency of the specialized trust region algorithm, when combined with our cubic modeling, to escape from local minimizers.|
|Editor:||Kluwer Academic Publishers|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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