The derivation of several item selection algorithms for use in fitting test items to target information functions is described. These algorithms circumvent iterative solutions by using the criteria of moving averages of the distance to a target information function and simultaneously considering an entire range of ability points used to condition the information functions. The algorithms were implemented in a microcomputer software package and tested by generating six forms of an American College Testing Program (ACT) mathematics test, each fit to an existing target test, including content-designated item subsets. Six forms of 40 items each were generated by ITEMSEL using the 600 items in the mathematics pool and the Mathematics Test Form 26A target information values conditional on K=31 quadrature points of theta. The results indicate that the algorithms provide reliable fit to the target in terms of item parameters, test information functions, and expected score distributions. A discussion of the application is included. Four tables and eight graphs present study data. A 11-item list of references is included. (Author/SLD)