http://dx.doi.org/10.1109/ICNC.2014.6975851">
 

Document Type

Conference Paper

Department/Unit

Department of Computer Science

Title

A direct search algorithm based on kernel density estimator for nonlinear optimization

Language

English

Abstract

© 2014 IEEE.In this paper, we propose a direct search algorithm based on kernel density estimator for the nonlinear optimization problems. It estimates the objective function by the kernel density estimator with the local samples only, and then approximates the ascent direction of the objective function with the one of the estimator. The proposed optimization approach features the derivative-free with much likely generating an ascent direction. We not only theoretically show that the search direction, which is used in the proposed algorithm towards maximizing the objective function, is the ascent direction of the objective function, but also empirically investigate the effectiveness of the search direction.

Publication Date

2014

Source Publication Title

2014 10th International Conference on Natural Computation (ICNC)

Start Page

297

End Page

302

Conference Location

Xiamen, China

Publisher

IEEE

ISBN (print)

9781479951505

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