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Directing the search of evolutionary and neighbourhood-search optimisers for the flowshop sequencing problem with an idle-time heuristic

  • Progress in Evolutionary Scheduling
  • Conference paper
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Evolutionary Computing (AISB EC 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1305))

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Abstract

This paper presents a heuristic for directing the neighbourhood (mutation operator) of stochastic optimisers, such as evolutionary algorithms, so to improve performance for the flowshop sequencing problem. Based on idle time, the heuristic works on the assumption that jobs that have to wait a relatively long time between machines are in an unsuitable position in the schedule and should be moved. The results presented here show that the heuristic improves performance, especially for problems with a large number of jobs. In addition the effectiveness of the heuristic and search in general was found to depend upon the neighbourhood structure in a consistent fashion across optimisers.

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Authors and Affiliations

  1. Department of Artificial Intelligence, University of Edinburgh, 80 South Bridge, EM1 1HN, Edinburgh, UK

    Peter Ross & Andrew Tuson

Authors
  1. Peter Ross
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  2. Andrew Tuson
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David Corne Jonathan L. Shapiro

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© 1997 Springer-Verlag Berlin Heidelberg

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Ross, P., Tuson, A. (1997). Directing the search of evolutionary and neighbourhood-search optimisers for the flowshop sequencing problem with an idle-time heuristic. In: Corne, D., Shapiro, J.L. (eds) Evolutionary Computing. AISB EC 1997. Lecture Notes in Computer Science, vol 1305. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0027176

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  • DOI: https://doi.org/10.1007/BFb0027176

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63476-8

  • Online ISBN: 978-3-540-69578-3

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