Producing robust schedules via an artificial immune system.

Hart, Emma, Ross, Peter and Nelson, Jeremy (1998) Producing robust schedules via an artificial immune system. In: Proceedings of International Conference on Evolutionary Computing. IEEE Computer Society Press, Anchorage, Alaska, pp. 464-469. ISBN 0-7803-4871-0

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    This paper describes an artificial immune system (AIS) approach
    to producing robust schedules for a dynamic jobshop
    scheduling problem in which jobs arrive continually,
    and the environment is subject to change due to practical
    reasons. We investigate whether an AIS can be evolved using
    a genetic algorithm, (GA), and then used to produce sets
    of schedules which together cover a range of contingencies,
    both foreseeable and unforeseeable. We compare the quality
    of the schedules to those produced using a genetic algorithm
    specifically designed for tackling job-shop scheduling
    problems, and find that the schedules produced from the
    evolved AIS compare favourably to those produced by the
    GA. Furthermore, we find that the AZS schedules are robust
    in that there are large similarities between each schedule in
    the set, indicating that a switch from one schedule to another
    could be performed with minimal disruption if rescheduling
    is required.

    Item Type: Book Section
    ISBN: 0-7803-4871-0
    Uncontrolled Keywords: artificial immune systems; job shop scheduling; genetic algorithm; antigens;
    University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Computing
    Dewey Decimal Subjects: 000 Computer science, information & general works > 000 Computer science, knowledge & systems > 006 Special Computer Methods > 006.3 Artificial intelligence
    Library of Congress Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Item ID: 3178
    Depositing User: Computing Research
    Date Deposited: 01 Sep 2010 16:51
    Last Modified: 15 Apr 2014 14:54

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