Alienor method for global optimization with a large number of variables

Abstract

Purpose

To show the usefulness of the Alienor method when applied to the global optimization problems that depend on large number of variables.

Design/methodology/approach

The approach is to use reducing transformations. The first is due to Cherruault and the second to Mora.

Findings

It was found that the Alienor method was very efficient and reliable in solving global optimization problems of many variables. Results produced to confirm this conclusion.

Research limitations/implications

The numerical results presented showed that the Alienor method was suitable for finding global minimum even in the case of a very large number of variables. The research provides a new methodology for solving such problems.

Practical implications

No other method, we believe, can obtain such results in so short a time for hundreds or even thousands of variables.

Originality/value

The new approach relies on the originality of both the Cherruault and the Mora transformations and their earlier invention of the Alienor method.

Citation

Benneouala, T. and Cherruault, Y. (2005), "Alienor method for global optimization with a large number of variables", Kybernetes, Vol. 34 No. 7/8, pp. 1104-1111. https://doi.org/10.1108/03684920510605911