Research Output

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

  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

  • Date:

    30 November 1997

  • Publication Status:

    Published

  • Publisher

    Springer-Verlag

  • DOI:

    10.1007/BFb0056926

  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    005 Computer programming, programs & data

Citation

Hart, E. & Ross, P. (1997). A heuristic combination method for solving job-shop scheduling problems. In Eiben, A. E., Back, T., Schoenauer, M. & Schwefel, H. (Eds.). Parallel Problem Solving from Nature V, 845-854. doi:10.1007/BFb0056926. ISBN 3-540-65078-4

Authors

Keywords

genetic algorithm, (GA); job-shop scheduling; heuristic combination;

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