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A multi-objective dynamic scheduling approach using multiple attribute decision making in semiconductor manufacturing

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Listed:
  • Yao, Shiqing
  • Jiang, Zhibin
  • Li, Na
  • Zhang, Huai
  • Geng, Na

Abstract

This paper proposes a multi-objective dynamic scheduling approach that combines three attributes based on a hybrid multiple attribute decision making (MADM) technique. With consideration of two kinds of uncertainties, three advanced attributes are specifically designed to optimize four key performance measures. Each attribute is converted into a relative closeness to the ideal alternative, and collaborate with the others at each scheduling instant. Furthermore, a cutoff method is used to make the proposed approach adapt to full-scale semiconductor manufacturing systems (SMSs) better. Results in two SMS models show that the proposed approach is validated for the real-time multi-objective scheduling problem.

Suggested Citation

  • Yao, Shiqing & Jiang, Zhibin & Li, Na & Zhang, Huai & Geng, Na, 2011. "A multi-objective dynamic scheduling approach using multiple attribute decision making in semiconductor manufacturing," International Journal of Production Economics, Elsevier, vol. 130(1), pages 125-133, March.
    • Handle: RePEc:eee:proeco:v:130:y:2011:i:1:p:125-133
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    References listed on IDEAS

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    1. R. W. Conway & W. L. Maxwell, 1962. "Network Dispatching by the Shortest-Operation Discipline," Operations Research, INFORMS, vol. 10(1), pages 51-73, February.
    2. Robert C. Leachman & Jeenyoung Kang & Vincent Lin, 2002. "SLIM: Short Cycle Time and Low Inventory in Manufacturing at Samsung Electronics," Interfaces, INFORMS, vol. 32(1), pages 61-77, February.
    3. Olafsson, Sigurdur & Li, Xiaonan, 2010. "Learning effective new single machine dispatching rules from optimal scheduling data," International Journal of Production Economics, Elsevier, vol. 128(1), pages 118-126, November.
    4. Wu, Muh-Cherng & Jiang, Jr-Hsiung & Chang, Wen-Jen, 2008. "Scheduling a hybrid MTO/MTS semiconductor fab with machine-dedication features," International Journal of Production Economics, Elsevier, vol. 112(1), pages 416-426, March.
    5. Wong, Bo K. & Lai, Vincent S., 2011. "A survey of the application of fuzzy set theory in production and operations management: 1998-2009," International Journal of Production Economics, Elsevier, vol. 129(1), pages 157-168, January.
    6. Thiesse, Frédéric & Fleisch, Elgar, 2008. "On the value of location information to lot scheduling in complex manufacturing processes," International Journal of Production Economics, Elsevier, vol. 112(2), pages 532-547, April.
    7. Vinod, V. & Sridharan, R., 2011. "Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system," International Journal of Production Economics, Elsevier, vol. 129(1), pages 127-146, January.
    8. Allahverdi, Ali & Soroush, H.M., 2008. "The significance of reducing setup times/setup costs," European Journal of Operational Research, Elsevier, vol. 187(3), pages 978-984, June.
    9. Yang, Taho & Chou, Pohung, 2005. "Solving a multiresponse simulation-optimization problem with discrete variables using a multiple-attribute decision-making method," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(1), pages 9-21.
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    Cited by:

    1. Yu-Fang Wang, 2020. "Adaptive job shop scheduling strategy based on weighted Q-learning algorithm," Journal of Intelligent Manufacturing, Springer, vol. 31(2), pages 417-432, February.
    2. Eduardo Fernández & Claudia Gómez-Santillán & Nelson Rangel-Valdez & Laura Cruz-Reyes, 2022. "Group Multi-Objective Optimization Under Imprecision and Uncertainty Using a Novel Interval Outranking Approach," Group Decision and Negotiation, Springer, vol. 31(5), pages 945-994, October.
    3. Fausto Balderas & Eduardo Fernandez & Claudia Gomez-Santillan & Nelson Rangel-Valdez & Laura Cruz, 2019. "An Interval-Based Approach for Evolutionary Multi-Objective Optimization of Project Portfolios," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1317-1358, July.

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