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 15:51
Last Modified: 15 Apr 2014 13:54

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