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A semantics-based dispatching rule selection approach for job shop scheduling

Author

Listed:
  • Heng Zhang

    (Syracuse University)

  • Utpal Roy

    (Syracuse University)

Abstract

Dispatching rules are commonly used for job shop scheduling in industries because they are easy to implement, and they yield reasonable solutions within a very short computational time. Many dispatching rules have been developed but they can only perform well in specific scenarios. This is because a dispatching rule or a combination of dispatching rules always pursues a single or multiple fixed production objectives. A lot of approaches (e.g. simulation based or machine learning based approaches) have been published in the literatures attempted to solve the problem of selecting the proper dispatching rules for a given production objective. To select a combination of dispatching rules per randomly selected combination of objectives, this paper investigates a novel semantics-based dispatching rule selection system. Each of the dispatching rules and production objectives relates to a set of scheduling parameters like processing time, remaining work, total work, due date, release date, tardiness, etc. These parameters are semantically interrelated so that a dispatching rule and a production objective can also be semantically related through their semantic expressions. A semantic similarity value can be calculated by comparing their semantic expressions. Based on this idea, a semantics-based dispatching rule selection system for job shop scheduling is developed to generate a combination of dispatching rules given randomly selected combination of production objectives. A proof-of-concept verification process is provided at the end of the paper.

Suggested Citation

  • Heng Zhang & Utpal Roy, 2019. "A semantics-based dispatching rule selection approach for job shop scheduling," Journal of Intelligent Manufacturing, Springer, vol. 30(7), pages 2759-2779, October.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:7:d:10.1007_s10845-018-1421-z
    DOI: 10.1007/s10845-018-1421-z
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    References listed on IDEAS

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    1. Jon K. Wilbrecht & William B. Prescott, 1969. "The Influence of Setup Time on Job Shop Performance," Management Science, INFORMS, vol. 16(4), pages 274-280, December.
    2. Jens Heger & Torsten Hildebrandt & Bernd Scholz-Reiter, 2015. "Dispatching rule selection with Gaussian processes," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(1), pages 235-249, March.
    3. S. S. Panwalkar & Wafik Iskander, 1977. "A Survey of Scheduling Rules," Operations Research, INFORMS, vol. 25(1), pages 45-61, February.
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    Cited by:

    1. Shiyong Yin & Jinsong Bao & Jie Zhang & Jie Li & Junliang Wang & Xiaodi Huang, 2020. "Real-time task processing for spinning cyber-physical production systems based on edge computing," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 2069-2087, December.
    2. Robson Flavio Castro & Moacir Godinho-Filho & Roberto Fernandes Tavares-Neto, 2022. "Dispatching method based on particle swarm optimization for make-to-availability," Journal of Intelligent Manufacturing, Springer, vol. 33(4), pages 1021-1030, April.

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