The Lazy Bureaucrat Scheduling Problem

TL;DR

This paper introduces 'Lazy Bureaucrat Problems,' a new class of scheduling problems where the worker aims to minimize work while remaining busy when possible, exploring the complexities of optimizing such 'perverse' schedules.

Contribution

It formalizes a novel class of scheduling problems focusing on minimal effort with constraints, highlighting differences between maximization and minimization in schedule optimization.

Findings

Defines the Lazy Bureaucrat Problems framework.

Analyzes preemptive and nonpreemptive settings.

Identifies new computational questions and complexities.

Abstract

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 worker's 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.