Proactive algorithms for scheduling with probabilistic durations
Beck, J. Christopher
International Joint Conferences on Artificial Intelligence (ICJAI)
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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