Several methods for optimal test construction from item banks have recently been proposed using information functions. The main problem with these methods is the large amount of time required to identify an optimal test. In this paper, a new method is presented for the Rasch model that considers groups of interchangeable items, instead of individual items. The process of item clustering is described, the cluster-based test construction model is outlined, and the computational procedure and results are given. Results indicate that this method produces accurate results in small amounts of time.