Proactive algorithms for scheduling with probabilistic durations

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Beck, J. Christopher
Wilson, Nic
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International Joint Conferences on Artificial Intelligence (ICJAI)
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Proactive scheduling seeks to generate high quality solutions despite execution time uncertainty. Building on work in [Beck and Wilson, 2004], we conduct an empirical study of a number of algorithms for the job shop scheduling problem with probabilistic durations. The main contributions of this paper are: the introduction and empirical analysis of a novel constraint-based search technique that can be applied beyond probabilistic scheduling problems, the introduction and empirical analysis of a number of deterministic filtering algorithms for probabilistic job shop scheduling, and the identification of a number of problem characteristics that contribute to algorithm performance.
Scheduling , Scheduling problem , Job shop scheduling problem , Deterministic scheduling algorithm , Classical scheduling formulation , Probabilistic problem , Constraint programming
Beck, J.C., and Wilson, N. (2005) 'Proactive Algorithms for Scheduling with Probabilistic Durations', IJCAI'05: Proceedings of the 19th International Joint Conference on Artificial intelligence, Edinburgh, Scotland, 30 July - 05 August, pp. 1201-1206
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