We introduce a new class of scheduling problems in which the optimization is performed by the worker (single ``machine) who performs the tasks. A typical workers objective is to minimize the amount of work he does (he is ``lazy), or more generally, to schedule as inefficiently (in some sense) as possible. The worker is subject to the constraint that he must be busy when there is work that he can do; we make this notion precise both in the preemptive and nonpreemptive settings. The resulting class of ``perverse scheduling problems, which we denote ``Lazy Bureaucrat Problems, gives rise to a rich set of new questions that explore the distinction between maximization and minimization in computing optimal schedules.
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