We introduce a new class of scheduling problems in which the optimization is performed by the worker (single “machine”) who
performs the tasks. The worker’s objective may be to minimize the amount of work he does (he is “lazy”). He is subject to
a constraint that he must be busy when there is work that he can do; we make this notion precise, particularly when preemption
is allowed. The resulting class of “perverse” scheduling problems, which we term “Lazy Bureaucrat Problems,” gives rise to
a rich set of new questions that explore the distinction between maximization and minimization in computing optimal schedules.
Partially supported by NSF (CCR-9732220).
Partially supported by Boeing, Bridgeport Machines, Sandia National Labs, Seagull Technologies, Sun Microsystems, and NSF
(CCR-9732220).
Partially supported by NSF (CCR-9625669), and ONR (431-0857A).