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Transfer-robot task scheduling in job shop

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  • Andy Ham

Abstract

This paper studies a simultaneous scheduling of production and material transfer in a job shop environment. The simultaneous scheduling approach has been recently adopted by warehouse operations, wherein transbots pick up jobs and deliver to pick-machines for processing that requires a simultaneous scheduling of jobs, transbots, and machines. However, both a large proportion of literature and real-world scheduling systems consider only one side of the problem. In our study, machines and transbot are both considered as constraining resources. The contributions of this paper are twofold. First, we propose a novel application of constraint programming for the job shop scheduling problem (JSP) with transbots, significantly outperforming all other benchmark approaches in the literature and proving optimality of the well-known benchmark instances, for the first time. Second, we propose a medium-scale benchmark instance.

Suggested Citation

  • Andy Ham, 2021. "Transfer-robot task scheduling in job shop," International Journal of Production Research, Taylor & Francis Journals, vol. 59(3), pages 813-823, February.
  • Handle: RePEc:taf:tprsxx:v:59:y:2021:i:3:p:813-823
    DOI: 10.1080/00207543.2019.1709671
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    Cited by:

    1. Hosseini, Amir & Otto, Alena & Pesch, Erwin, 2024. "Scheduling in manufacturing with transportation: Classification and solution techniques," European Journal of Operational Research, Elsevier, vol. 315(3), pages 821-843.
    2. Dalila B. M. M. Fontes & S. Mahdi Homayouni & Mauricio G. C. Resende, 2022. "Job-shop scheduling-joint consideration of production, transport, and storage/retrieval systems," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1284-1322, September.
    3. Fatemi-Anaraki, Soroush & Tavakkoli-Moghaddam, Reza & Foumani, Mehdi & Vahedi-Nouri, Behdin, 2023. "Scheduling of Multi-Robot Job Shop Systems in Dynamic Environments: Mixed-Integer Linear Programming and Constraint Programming Approaches," Omega, Elsevier, vol. 115(C).

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