Abstract
Knowledge-worker development projects are often performed where multiple projects are always in progress, and where preemption often occurs for solving time-critical customer service projects. The following nonlinear model for learning-intense situations demonstrates that the choice of preemption policy significantly impacts project completion times. Within this model, the authors identify policies that reduce the detrimental effects of preemption. The best policy preempts the activity that has the most slack and has been in progress the shortest time, and restarts the activity quickly with qualified resources as soon as possible.
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