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An iterative approach for the serial batching problem with parallel machines and job families

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  • Liji Shen
  • Lars Mönch
  • Udo Buscher

Abstract

In this paper, we consider a parallel machine scheduling problem to minimize the total completion time. Each job belongs to a certain family. All jobs of one family have identical processing times. Major setups occur between jobs of different families, and we include sequence dependencies. Batches of jobs belonging to the same family can be formed to avoid these setups. Furthermore, we assume serial batching and batch availability. Therefore, the processing time of a batch is the sum of the processing times of all jobs grouped into the corresponding batch. An iterative method is developed for solving this specific problem. This approach alternates between varying batch sizes using an efficient heuristic and sequencing batches based on variable neighborhood search (VNS). Computational results demonstrate that the iterative heuristic outperforms heuristics based on a fixed batch size and list scheduling. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • Liji Shen & Lars Mönch & Udo Buscher, 2013. "An iterative approach for the serial batching problem with parallel machines and job families," Annals of Operations Research, Springer, vol. 206(1), pages 425-448, July.
    • Handle: RePEc:spr:annopr:v:206:y:2013:i:1:p:425-448:10.1007/s10479-013-1339-y
    DOI: 10.1007/s10479-013-1339-y
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    References listed on IDEAS

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    Cited by:

    1. Yi Tan & Lars Mönch & John W. Fowler, 2018. "A hybrid scheduling approach for a two-stage flexible flow shop with batch processing machines," Journal of Scheduling, Springer, vol. 21(2), pages 209-226, April.
    2. Lin-Hui Sun & Kai Cui & Ju-Hong Chen & Jun Wang & Xian-Chen He, 2013. "Research on permutation flow shop scheduling problems with general position-dependent learning effects," Annals of Operations Research, Springer, vol. 211(1), pages 473-480, December.
    3. Mehdi Rajabi Asadabadi, 2017. "A developed slope order index (SOI) for bottlenecks in projects and production lines," Computational Management Science, Springer, vol. 14(2), pages 281-291, April.
    4. Jun-Ho Lee & Hyun-Jung Kim, 2021. "A heuristic algorithm for identical parallel machine scheduling: splitting jobs, sequence-dependent setup times, and limited setup operators," Flexible Services and Manufacturing Journal, Springer, vol. 33(4), pages 992-1026, December.

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