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Solving constrained global optimization problems without penalty parameters

Solving constrained global optimization problems without penalty parameters Purpose – To propose a new method for solving constrained global optimization problems using a method that consists of transforming a constrained global optimization problem into an unconstrained one without using any penalty coefficients. Design/methodology/approach – Use of an unconstrained global optimization method such as the Alienor method which has been adapted for several variables. Findings – Use of the adapted Alienor method allowed the solution of the transformed problem with little difficulty. Research limitations/implications – Transforms the original objective function into a new one involves the introduction of some extra parameters. Cannot guarantee the convergence to a global solution of the original problem. The simple described approach, provides new possibilities. Practical implications – No further parameters introduced in this new approach, and no conditions or hypotheses are imposed on the objective function or on the constraints. Originality/value – New method of transforming a constrained problem into an unconstrained one, with use of proven Alienor method adapted to several variables. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Kybernetes Emerald Publishing

Solving constrained global optimization problems without penalty parameters

Balira O. Konfe; Yves Cherruault; Blaise Some
Kybernetes , Volume 34 (7/8): 14 – Aug 1, 2005
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References (14)

Publisher
Emerald Publishing
Copyright
Copyright © 2005 Emerald Group Publishing Limited. All rights reserved.
ISSN
0368-492X
DOI
10.1108/03684920510605902
Publisher site
See Article on Publisher Site

Abstract

Purpose – To propose a new method for solving constrained global optimization problems using a method that consists of transforming a constrained global optimization problem into an unconstrained one without using any penalty coefficients. Design/methodology/approach – Use of an unconstrained global optimization method such as the Alienor method which has been adapted for several variables. Findings – Use of the adapted Alienor method allowed the solution of the transformed problem with little difficulty. Research limitations/implications – Transforms the original objective function into a new one involves the introduction of some extra parameters. Cannot guarantee the convergence to a global solution of the original problem. The simple described approach, provides new possibilities. Practical implications – No further parameters introduced in this new approach, and no conditions or hypotheses are imposed on the objective function or on the constraints. Originality/value – New method of transforming a constrained problem into an unconstrained one, with use of proven Alienor method adapted to several variables.

Journal

Kybernetes – Emerald Publishing

Published: Aug 1, 2005

Keywords: Cybernetics; Optimization techniques; Numerical analysis

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