We present an algorithm for finding a global minimum of a multimodal, multivariate functionwhose evaluation is very expensive, affected by noise andwhose derivatives are not available. The proposed algorithm is a new version of the well known Price’s algorithm and its distinguishing feature is that it tries to employ as much as possible the information about the objective function obtained at previous iterates. The algorithm has been tested on a large set of standard test problems and it has shown a satisfactory computational behaviour. The proposed algorithm has been used to solve efficiently some difficult optimization problems deriving from the study of eclipsing binary star light curves.
A new version of the Price's algorithm for global optimization / P., Brachetti; M., De Felice Ciccoli; DI PILLO, Gianni; Lucidi, Stefano. - In: JOURNAL OF GLOBAL OPTIMIZATION. - ISSN 0925-5001. - STAMPA. - 10:(1997), pp. 165-184. [10.1023/a:1008250020656]
A new version of the Price's algorithm for global optimization
DI PILLO, Gianni;LUCIDI, Stefano
1997
Abstract
We present an algorithm for finding a global minimum of a multimodal, multivariate functionwhose evaluation is very expensive, affected by noise andwhose derivatives are not available. The proposed algorithm is a new version of the well known Price’s algorithm and its distinguishing feature is that it tries to employ as much as possible the information about the objective function obtained at previous iterates. The algorithm has been tested on a large set of standard test problems and it has shown a satisfactory computational behaviour. The proposed algorithm has been used to solve efficiently some difficult optimization problems deriving from the study of eclipsing binary star light curves.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
