# American Institute of Mathematical Sciences

2015, 5(2): 169-184. doi: 10.3934/naco.2015.5.169

## A wedge trust region method with self-correcting geometry for derivative-free optimization

 1 School of Mathematical Sciences, Jiangsu Key Labratory for NSLSCS, Nanjing Normal University, Nanjing 210023, China, China 2 PPGEPS, Pontifical Catholic University of Parana (PUCPR), Curitiba, Parana, Brazil 3 Department of Mathematics, Universidade Federal do Parana (UFPR), Curitiba, Parana, Brazil

Received  December 2014 Revised  April 2015 Published  June 2015

Recently, some methods for solving optimization problems without derivatives have been proposed. The main part of these methods is to form a suitable model function that can be minimized for obtaining a new iterative point. An important strategy is geometry-improving iteration for a good model, which needs a lot of calculations. Besides, Marazzi and Nocedal (2002) proposed a wedge trust region method for derivative free optimization. In this paper, we propose a new self-correcting geometry procedure with less computational efforts, and combine it with the wedge trust region method. The global convergence of new algorithm is established. The limited numerical experiments show that the new algorithm is efficient and competitive.
Citation: Liang Zhang, Wenyu Sun, Raimundo J. B. de Sampaio, Jinyun Yuan. A wedge trust region method with self-correcting geometry for derivative-free optimization. Numerical Algebra, Control and Optimization, 2015, 5 (2) : 169-184. doi: 10.3934/naco.2015.5.169
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##### References:
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