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Synthesis of Scheduling Heuristics by Composition and Recombination

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Optimization and Learning (OLA 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1443))

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Abstract

In many machine scheduling studies, individual algorithms for each problem have been developed to cope with the specifics of the problem. On the other hand, the same underlying fundamentals (e.g. Shortest Processing Time, Local Search) are often used in the algorithms and only slightly modified for the different problems. This paper deals with the synthesis of machine scheduling algorithms from components of a repository. Especially flow shop and job shop problems with makespan objective are considered to solve with Shortes/Longest Processing Time, NEH, Giffler & Thompson algorithms. For these components, the paper includes an exemplary implementation of an agile scheduling system that uses the Combinatory Logic Synthesizer to recombine components of scheduling algorithms to solve a given scheduling problem. Special attention is given to the composition heuristics and the process of recombination to executable programs. The advantages of this componentization are discussed and illustrated with examples. It will be shown that algorithms can be generalized to deal with scheduling problems of different machine environments and production constraints.

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Author information

Authors and Affiliations

  1. Department of Computer Science 14 – Software Engineering, TU Dortmund University, Dortmund, Germany

    Dominik Mäckel & Jan Winkels

  2. Department of Computer Science 4 – Modeling and Simulation, TU Dortmund University, Dortmund, Germany

    Christin Schumacher

Authors
  1. Dominik Mäckel
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  2. Jan Winkels
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  3. Christin Schumacher
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Corresponding author

Correspondence to Christin Schumacher .

Editor information

Editors and Affiliations

  1. University of Cádiz, Cádiz, Spain

    Bernabé Dorronsoro

  2. University of Technology of Troyes, Troyes, France

    Lionel Amodeo

  3. University of Catania, Catania, Italy

    Mario Pavone

  4. University of Cádiz, Cádiz, Spain

    Patricia Ruiz

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Mäckel, D., Winkels, J., Schumacher, C. (2021). Synthesis of Scheduling Heuristics by Composition and Recombination. In: Dorronsoro, B., Amodeo, L., Pavone, M., Ruiz, P. (eds) Optimization and Learning. OLA 2021. Communications in Computer and Information Science, vol 1443. Springer, Cham. https://doi.org/10.1007/978-3-030-85672-4_21

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  • DOI: https://doi.org/10.1007/978-3-030-85672-4_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-85671-7

  • Online ISBN: 978-3-030-85672-4

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