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Hybrid dispatching and genetic algorithm for the surface mount technology scheduling problem in semiconductor factories

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  • Wang, Hung-Kai
  • Yang, Ting-Yun
  • Wang, Ya-Han
  • Wu, Chia-Le
Abstract
Surface mount technology (SMT) is widely used in semiconductor packaging factories to assemble electronic components onto printed circuit boards. Therefore, reducing bottlenecks in SMT implementation is crucial for achieving the optimal production efficiency and meeting customer demands in semiconductor factories. This study developed a hybrid dispatching and genetic algorithm (HDGA) which uses a genetic algorithm (GA) and dispatch rules, to reduce machine set-up times and increase delivery fulfillment rates. The proposed HDGA is embedded in a scheduling system to optimize production scheduling by considering all practical constraints associated with SMT implementation, such as machine and job statuses, lot consolidation constraints, processing time, works in progress and machine priority, multiple processing rounds, and issue-number-related constraints. To validate the effectiveness of this algorithm, the present study compared its performance with that of a traditional GA and a hybrid GA. The results indicated that the HDGA outperformed the other three algorithms. The proposed algorithm can improve productivity, product quality, product delivery rates, and overall scheduling efficiency in semiconductor factories.

Suggested Citation

  • Wang, Hung-Kai & Yang, Ting-Yun & Wang, Ya-Han & Wu, Chia-Le, 2025. "Hybrid dispatching and genetic algorithm for the surface mount technology scheduling problem in semiconductor factories," International Journal of Production Economics, Elsevier, vol. 280(C).
    • Handle: RePEc:eee:proeco:v:280:y:2025:i:c:s0925527324003578
    DOI: 10.1016/j.ijpe.2024.109500
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    References listed on IDEAS

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    1. Charles, Vincent & Kumar, Mukesh & Irene Kavitha, S., 2012. "Measuring the efficiency of assembled printed circuit boards with undesirable outputs using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 136(1), pages 194-206.
    2. Yu, Tae-Sun & Han, Jun-Hee, 2021. "Scheduling proportionate flow shops with preventive machine maintenance," International Journal of Production Economics, Elsevier, vol. 231(C).
    3. Berti, Nicola & Finco, Serena & Battaïa, Olga & Delorme, Xavier, 2021. "Ageing workforce effects in Dual-Resource Constrained job-shop scheduling," International Journal of Production Economics, Elsevier, vol. 237(C).
    4. 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.
    5. Wichmann, Matthias Gerhard & Johannes, Christoph & Spengler, Thomas Stefan, 2019. "Energy-oriented Lot-Sizing and Scheduling considering energy storages," International Journal of Production Economics, Elsevier, vol. 216(C), pages 204-214.
    6. Shabtay, Dvir & Mosheiov, Gur & Oron, Daniel, 2022. "Single machine scheduling with common assignable due date/due window to minimize total weighted early and late work," European Journal of Operational Research, Elsevier, vol. 303(1), pages 66-77.
    7. Dauzère-Pérès, Stéphane & Ding, Junwen & Shen, Liji & Tamssaouet, Karim, 2024. "The flexible job shop scheduling problem: A review," European Journal of Operational Research, Elsevier, vol. 314(2), pages 409-432.
    8. Nduhura Munga, Justin & Dauzère-Pérès, Stéphane & Yugma, Claude & Vialletelle, Philippe, 2015. "A mathematical programming approach for optimizing control plans in semiconductor manufacturing," International Journal of Production Economics, Elsevier, vol. 160(C), pages 213-219.
    9. Huang, Kerry & Wang, Kedi & Lee, Peter K.C. & Yeung, Andy C.L., 2023. "The impact of industry 4.0 on supply chain capability and supply chain resilience: A dynamic resource-based view," International Journal of Production Economics, Elsevier, vol. 262(C).
    10. Tzu-Yen Hong & Chen-Fu Chien, 2020. "A simulation-based dynamic scheduling and dispatching system with multi-criteria performance evaluation for Industry 3.5 and an empirical study for sustainable TFT-LCD array manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 58(24), pages 7531-7547, December.
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