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A Diversity Based Multi-objective Hyper-heuristic for the FJSP with Sequence-Dependent Set-Up Times, Auxiliary Resources and Machine Down Time

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Progress in Artificial Intelligence (EPIA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11805))

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Abstract

In this paper a diversity based multi-objective hyper-heuristic (MOO-HMHH) algorithm for the flexible job shop scheduling problem (FJSP) with sequence-dependent set-up times (SDST), auxiliary resources and machine down time is analyzed. The algorithm is evaluated on real customer datasets to determine the impact of machine breakdown intervals and due dates on algorithm performance. The diversity based hyper-heuristic algorithm compared well to two other hyper-heuristic algorithms and to its constituent algorithms and promising results were obtained with respect to the increased generality of the hyper-heuristics.

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Authors and Affiliations

  1. Department of Industrial Engineering, Stellenbosch University, Stellenbosch, South Africa

    Jacomine Grobler

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  1. Jacomine Grobler
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Correspondence to Jacomine Grobler .

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Editors and Affiliations

  1. INESC-TEC, University of Trás-os-Montes and Alto Douro, Vila Real, Portugal

    Paulo Moura Oliveira

  2. University of Minho, Braga, Portugal

    Paulo Novais

  3. LIACC/UP, University of Porto, Porto, Portugal

    Luís Paulo Reis

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Grobler, J. (2019). A Diversity Based Multi-objective Hyper-heuristic for the FJSP with Sequence-Dependent Set-Up Times, Auxiliary Resources and Machine Down Time. In: Moura Oliveira, P., Novais, P., Reis, L. (eds) Progress in Artificial Intelligence. EPIA 2019. Lecture Notes in Computer Science(), vol 11805. Springer, Cham. https://doi.org/10.1007/978-3-030-30244-3_13

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  • DOI: https://doi.org/10.1007/978-3-030-30244-3_13

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  • Online ISBN: 978-3-030-30244-3

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