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Conference Papers Year : 2018

Scheduling under Uncertainty: A Query-based Approach

Evripidis Bampis
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Alexander Kononov
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Pierre Sens


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.
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hal-01924648 , version 1 (16-11-2018)



Luciana Arantes, Evripidis Bampis, Alexander Kononov, Manthos Letsios, Giorgio Lucarelli, et al.. Scheduling under Uncertainty: A Query-based Approach. IJCAI 2018 - 27th International Joint Conference on Artificial Intelligence, Jul 2018, Stockholm, Sweden. pp.4646-4652, ⟨10.24963/ijcai.2018/646⟩. ⟨hal-01924648⟩
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