Search results

1 – 3 of 3
Per page
102050
Citations:
Loading...
Access Restricted. View access options
Article
Publication date: 1 August 2005

Abdelkader Ziadi, Samia Khelladi and Yves Cherruault

Classical multidimensional global optimization methods are difficult to implement in high dimensions. To show that the Alienor method coupled with the Brent algorithm can avoid…

200

Abstract

Purpose

Classical multidimensional global optimization methods are difficult to implement in high dimensions. To show that the Alienor method coupled with the Brent algorithm can avoid this difficulty.

Design/methodology/approach

Use is made of the Alienor method and the Brent algorithm to obtain algorithms that were applied to test functions having several local minima.

Findings

Interesting results concerning the number of evaluation points were obtained. It was shown that this coupling can be improved if α‐dense curves of minimal length were used.

Research limitations/implications

Multidimensional global optimization problems have proven to be difficult to implement in high dimensions. This research continues the search for improved methods by coupling existing established methods such as Alienor with others such as the Brent algorithm.

Originality/value

A new coupled method has been developed and algorithms obtained to tackle such global optimization problems. The coupling is unique and the algorithms are tested numerically on selected functions.

Details

Kybernetes, vol. 34 no. 7/8
Type: Research Article
ISSN: 0368-492X

Keywords

Access Restricted. View access options
Article
Publication date: 1 August 2005

Abdelkader Ziadi, Djaouida Guettal and Yves Cherruault

Aims to present study of the coupling of the Alienor method with the algorithm of Piyavskii‐Shubert for global optimization applications.

252

Abstract

Purpose

Aims to present study of the coupling of the Alienor method with the algorithm of Piyavskii‐Shubert for global optimization applications.

Design/methodology/approach

The Alienor method allows us to transform a multivariable function into a function of a single variable for which it is possible to use an efficient and rapid method for calculating the global optimum. This simplification is based on the use of the established Alienor methodology.

Findings

The Alienor method allows us to transform a multidimensional problem into a one‐dimensional problem of the same type. It was then possible to use the Piyavskii‐Shubert method based on sub‐estimators of the objectives function. The obtained algorithm from coupling the two methods was found to be simple and easy to implement on any multivariable function.

Research limitations/implications

This method does not require derivatives and the convergence of the algorithm is relatively rapid if the Lipschitz constant is small.

Practical implications

The classical multidimensional global optimization methods involve great difficulties for their implementation to high dimensions. The coupling of two established methods produces a practical easy to implement technique.

Originality/value

New method couples two established ones and produces a simple and user‐friendly technique.

Details

Kybernetes, vol. 34 no. 7/8
Type: Research Article
ISSN: 0368-492X

Keywords

Available. Content available
Article
Publication date: 1 August 2005

51

Abstract

Details

Kybernetes, vol. 34 no. 7/8
Type: Research Article
ISSN: 0368-492X

1 – 3 of 3
Per page
102050