Sphere Operators and Their Applicability for Constrained Parameter Optimization Problems

In this paper we continue our earlier studies [13, 14] on boundary operators for constrained parameter optimization problems. The significance of this line of research is based on the observation that usually the global solution for many optimization problems lies on the boundary of the feasible region. Thus, for many constrained numerical optimization problems it might be beneficial to search just the boundary of the search space defined by a set of constraints (some other algorithm might be used for searching the interior of the search space, if activity of a constraint is not certain). We discuss one particular class of boundary operators — sphere operators — and discuss their applicability to some constrained problems (with convex feasible search spaces) through a mapping between the boundary of the feasible region of the search space and a sphere. We provide also with some experimental evaluation of these transformations.