Abstract
In this paper, we propose a optimization technique that we call a hierarchical Response Surface Methodology (hRSM). Since it is difficult to approximate a complex parameter space by using a single quadratic polynomial surface, hRSM adopted a recursive sub division technique and used the coefficient of multiple determinations (R2) to represent the response surface in each sub space for the threshold of the sub division. We verified the accuracy of hRSM by using some well-known benchmark functions that a reused in optimization. We confirmed the effectiveness of hRSM by applying it to bio-simulation's parameter estimation.
