ECAI 2004 Conference Paper

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Job Shop Scheduling with Probabilistic Durations

J. Christopher Beck, Nic Wilson

Proactive approaches to scheduling take into account information about the execution time uncertainty of a scheduling problem in forming a schedule. In this paper, we investigate proactive approaches for the job shop scheduling problem where activity durations are random variables. The main contributions are (i) the introduction of the problem of finding probabilistic execution guarantees for difficult scheduling problems; (ii) a method for generating a lower bound on the minimal makespan; (iii) the development of the Monte Carlo approach for evaluating solutions; and (iv) the design and empirical analysis of three solution techniques: an approximately complete technique, found to be feasible only for very small problems, and two techniques based on finding good solutions to a deterministic scheduling problem, which scale to much larger problems.

Keywords: Scheduling, Probabilistic Reasoning, Reasoning under Uncertainty

Citation: J. Christopher Beck, Nic Wilson: Job Shop Scheduling with Probabilistic Durations. In R.López de Mántaras and L.Saitta (eds.): ECAI2004, Proceedings of the 16th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2004, pp.652-656.


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ECAI-2004 is organised by the European Coordinating Committee for Artificial Intelligence (ECCAI) and hosted by the Universitat Politècnica de València on behalf of Asociación Española de Inteligencia Artificial (AEPIA) and Associació Catalana d'Intel-ligència Artificial (ACIA).