Computer-assisted test assembly using optimization heuristics

Numerous algorithms and heuristics have been introduced that allow test developers to simultaneously generate multiple test forms that match qualitative constraints, such as content blueprints, and quantitative targets, such as test information functions. A variation of a greedy algorithm is presented here that can be used in a wide range of test assembly problems. The algorithm selects items to have a locally optimal fit to a moving set of average criterion values. A normalization procedure is used to allow the heuristic to work simultaneously with numerous qualitative and quantitative constraints. A complex sample application is demonstrated.