In this paper, we present a hierarchical approach for constraint transformation. The important features of this are: a genetic algorithm ({\small GA}) based search engine that computes design parameter ranges, a hierarchically organized characterization mechanism based on the concept of directed intervals that assists the search engine and an analog performance estimator. Experiments were conducted comparing the hierarchical approach with a flat bottom-up one. The results obtained demonstrate the effectiveness of the former approach. Experimental results highlighting the impact of using the characterization information within the constraint transformation process are also presented.