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A heuristic combination method for solving job-shop scheduling problems.

Hart, Emma and Ross, Peter (1998) A heuristic combination method for solving job-shop scheduling problems. In: Parallel Problem Solving from Nature V. Lecture Notes in Computer Science, 1498 . Springer-Verlag, pp. 845-854. ISBN 3-540-65078-4

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Abstract/Description

This paper describes a heuristic combination based genetic algorithm, (GA), for tackling dynamic job-shop scheduling problems. Our approach is novel in that the genome encodes a choice of algorithm to be used to produce a set of schedulable operations, alongside a choice of heuristic which is used to choose an operation from the resulting set. We test the approach on 12 instances of dynamic problems, using 4 different objectives to judge schedule quality. We find that our approach outperforms other heuristic combination methods, and also performs well compared to the most recently published results on a number of benchmark problems

Item Type: Book Section
ISBN: 3-540-65078-4
Electronic ISBN: 978-3-540-49672-4
Additional Information: 5th International Conference Amsterdam, The Netherlands September 27–30, 1998 Proceedings
Uncontrolled Keywords: genetic algorithm, (GA); job-shop scheduling; heuristic combination;
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 > 005 Computer programming, programs & data
Library of Congress Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Item ID: 3180
Depositing User: Computing Research
Date Deposited: 27 Aug 2010 11:58
Last Modified: 15 Apr 2014 14:52
URI: http://researchrepository.napier.ac.uk/id/eprint/3180

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