A new auxiliary function method for general constrained global optimization

Abstract

In this article, we first propose a method to obtain an approximate feasible point for general constrained global optimization problems (with both inequality and equality constraints). Then we propose an auxiliary function method to obtain a global minimizer or an approximate global minimizer with a required precision for general global optimization problems by locally solving some unconstrained programming problems. Some numerical examples are reported to demonstrate the efficiency of the present optimization method.

Keywords:

• auxiliary function method
• general constrained global optimization

AMS Subject Classifications::

• 90C26
• 90C30

Acknowledgements

This work is jointly supported by the Australian Research Council under Grant DP0771709, the National Natural Science Foundation of China under Grant 10971241 and the Alexander von Humboldt Foundation.