Scheduling under Uncertainty: A Query-based Approach

Author:

Arantes Luciana1,Bampis Evripidis1,Kononov Alexander23,Letsios Manthos1,Lucarelli Giorgio4,Sens Pierre1

Affiliation:

1. Sorbonne Université, CNRS, Laboratoire d'Informatique de Paris 6, LIP6, F-75005 Paris, France

2. Sobolev Institute of Mathematics, Novosibirsk, Russia

3. Novosibirsk State University, Department of Mechanics and Mathematics, Russia

4. Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, LIG, 38000 Grenoble, France

Abstract

We consider a single machine, a set of unit-time jobs, and a set of unit-time errors. We assume that the time-slot at which each error will occur is not known in advance but, for every error, there exists an uncertainty area during which the error will take place. In order to find if the error occurs in a specific time-slot, it is necessary to issue a query to it. In this work, we study two problems: (i) the error-query scheduling problem, whose aim is to reveal enough error-free slots with the minimum number of queries, and (ii) the lexicographic error-query scheduling problem where we seek the earliest error-free slots with the minimum number of queries. We consider both the off-line and the on-line versions of the above problems. In the former, the whole instance and its characteristics are known in advance and we give a polynomial-time algorithm for the error-query scheduling problem. In the latter, the adversary has the power to decide, in an on-line way, the time-slot of appearance for each error. We propose then both lower bounds and algorithms whose competitive ratios asymptotically match these lower bounds.

Publisher

International Joint Conferences on Artificial Intelligence Organization

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Round-Competitive Algorithms for Uncertainty Problems with Parallel Queries;Algorithmica;2022-09-15

2. Speed Scaling with Explorable Uncertainty;Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures;2021-07-06

3. Explorable Uncertainty Meets Decision-Making in Logistics;Dynamics in Logistics;2021

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