Numerous algorithms and heuristics have be en in-troduced that allow test developers to simultan eously generate multiple test forms that match quali tative constraints, such as content blueprint s, and titative targets, such as test information func tions. A variation of a greedy algorithm is presente d here that can be used in a wide range of test as sembly 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.
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