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A simulation-based study of dispatching rules in a dynamic job shop scheduling problem with batch release and extended technical precedence constraints

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  • Xiong, Hegen
  • Fan, Huali
  • Jiang, Guozhang
  • Li, Gongfa

Abstract

This paper considers a simulation-based analysis of dispatching rules for scheduling in a dynamic job shop with batch release taking into account the extended technical precedence constraint which is a new term defined as the extension of conventional routing-based technical precedence constraint in our paper. With respect to tardiness-related measures, the relative performances of some widely-used dispatching rules as well as four new ones proposed in our paper are evaluated for different settings of the model parameters. The results of the simulation study demonstrate the effectiveness of the four new proposed dispatching rules, and also reveal that the relative performance of dispatching rules can be affected by some model parameters. For the standard job shop scheduling problem model, where there are no extended technical precedence constraints between jobs, as well as for the models taking into account the extended technical precedence constraint, it is shown that for minimizing the total tardiness and the percentage of tardy jobs, the four new proposed dispatching rules are very effective under relatively loose due date. With respect to tardiness-related objectives, the relative performance of the analyzed dispatching rules can be affected by changing not only the levels of the extended technical precedence constraint, but also the due date tightness.

Suggested Citation

  • Xiong, Hegen & Fan, Huali & Jiang, Guozhang & Li, Gongfa, 2017. "A simulation-based study of dispatching rules in a dynamic job shop scheduling problem with batch release and extended technical precedence constraints," European Journal of Operational Research, Elsevier, vol. 257(1), pages 13-24.
    • Handle: RePEc:eee:ejores:v:257:y:2017:i:1:p:13-24
    DOI: 10.1016/j.ejor.2016.07.030
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    3. Ferreira, Cristiane & Figueira, Gonçalo & Amorim, Pedro, 2022. "Effective and interpretable dispatching rules for dynamic job shops via guided empirical learning," Omega, Elsevier, vol. 111(C).
    4. Toly Chen & Li-Chih Wang & Min-Chi Chiu, 2018. "A multi-granularity approach for estimating the sustainability of a factory simulation model: semiconductor packaging as an example," Operational Research, Springer, vol. 18(3), pages 711-729, October.
    5. Ahmet Kursad Turker & Adnan Aktepe & Ali Firat Inal & Olcay Ozge Ersoz & Gulesin Sena Das & Burak Birgoren, 2019. "A Decision Support System for Dynamic Job-Shop Scheduling Using Real-Time Data with Simulation," Mathematics, MDPI, vol. 7(3), pages 1-19, March.
    6. Schaller, Jeffrey & Valente, Jorge M.S., 2020. "Minimizing total earliness and tardiness in a nowait flow shop," International Journal of Production Economics, Elsevier, vol. 224(C).
    7. Hankun Zhang & Borut Buchmeister & Xueyan Li & Robert Ojstersek, 2023. "An Efficient Metaheuristic Algorithm for Job Shop Scheduling in a Dynamic Environment," Mathematics, MDPI, vol. 11(10), pages 1-24, May.

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