The filled function transformations for constrained global optimization

We have found that filled function transformations are very useful in unconstrained global optimization. This paper is concerned with constrained global optimization problems, and we find several possible ways to find a global solution of such a problem by using a filled function transformation. The investigation indicates that using the usual filled function with the original constraints to solve a sequence of constrained local optimization problems is a good approach.