A hybrid trust region algorithm for unconstrained optimizationstar, open

• Autores: Yigui Ou
• Localización: Applied numerical mathematics, ISSN-e 0168-9274, Vol. 61, Nº. 7, 2011, págs. 900-909
• Idioma: inglés
• DOI: 10.1016/j.apnum.2011.03.002
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• Resumen

  • This paper presents a hybrid trust region algorithm for unconstrained optimization problems. It can be regarded as a combination of ODE-based methods, line search and trust region techniques. A feature of the proposed method is that at each iteration, a system of linear equations is solved only once to obtain a trial step. Further, when the trial step is not accepted, the method performs an inexact line search along it instead of resolving a new linear system. Under reasonable assumptions, the algorithm is proven to be globally and superlinearly convergent. Numerical results are also reported that show the efficiency of this proposed method.