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Determining optimal batch interval and production strategy based on available-to-promise model for order promising

Author

Listed:
  • Lu-Wen Liao

    (National Taichung University of Science and Technology)

  • Yu-Chung Tsao

    (National Taiwan University of Science and Technology
    National Taiwan University of Science and Technology)

  • Yu-Han Hung

    (Fu Chun Shin Machinery Manufacture Co., Ltd.)

Abstract

With the intensification of market competition, rapid changes in customer demand in the era of globalization, and uncertainty in the supply chain, manufacturers are facing increasing challenges in responding to customer requests on time. Available-to-promise (ATP) is a system that provides product availability information for promising customer order requests by considering the tradeoff between customer satisfaction and supply chain efficiency. This paper proposes a mixed integer programming model based on ATP theory to obtain the optimal batch interval length and production strategy of bill of material items. The objective of the proposed model is to maximize the manufacturer’s profit. Experimental data is analyzed to investigate the impact of the batch interval length and production strategies adopted by the manufacturer on its profit. The results provide theoretical guidance and implementation methods for manufacturers to maximize profits.

Suggested Citation

  • Lu-Wen Liao & Yu-Chung Tsao & Yu-Han Hung, 2025. "Determining optimal batch interval and production strategy based on available-to-promise model for order promising," Annals of Operations Research, Springer, vol. 349(1), pages 315-338, June.
    • Handle: RePEc:spr:annopr:v:349:y:2025:i:1:d:10.1007_s10479-023-05641-7
    DOI: 10.1007/s10479-023-05641-7
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    References listed on IDEAS

    as
    1. Lei Xu & Jing Chen, 2021. "Real-time order allocation model by considering available-to-promise reserving, occupying and releasing mechanisms," International Journal of Production Research, Taylor & Francis Journals, vol. 59(2), pages 429-443, January.
    2. Gössinger, Ralf & Kalkowski, Sonja, 2015. "Robust order promising with anticipated customer response," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 529-542.
    3. Zhenying Zhao & Michael Ball & Masahiro Kotake, 2005. "Optimization-Based Available-To-Promise with Multi-Stage Resource Availability," Annals of Operations Research, Springer, vol. 135(1), pages 65-85, March.
    4. Armindo Soares & Carina Pimentel & Ana Moura, 2022. "Production planning and scheduling with applications in the tile industry," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 44(1), pages 58-79.
    5. Pibernik, Richard, 2005. "Advanced available-to-promise: Classification, selected methods and requirements for operations and inventory management," International Journal of Production Economics, Elsevier, vol. 93(1), pages 239-252, January.
    6. Chien-Yu Chen & Zhen-Ying Zhao & Michael O. Ball, 2001. "Quantity and Due Date Quoting Available to Promise," Information Systems Frontiers, Springer, vol. 3(4), pages 477-488, December.
    7. Stadtler, Hartmut & Kilger, C., 2000. "Supply chain management and advanced planning: concepts, models, software and case studies," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 4691, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Alexander Seitz & Martin Grunow, 2017. "Increasing accuracy and robustness of order promises," International Journal of Production Research, Taylor & Francis Journals, vol. 55(3), pages 656-670, February.
    9. Xiong, M.H. & Tor, S.B. & Bhatnagar, Rohit & Khoo, L.P. & Venkat, S., 2006. "A DSS approach to managing customer enquiries for SMEs at the customer enquiry stage," International Journal of Production Economics, Elsevier, vol. 103(1), pages 332-346, September.
    10. Olhager, Jan, 2003. "Strategic positioning of the order penetration point," International Journal of Production Economics, Elsevier, vol. 85(3), pages 319-329, September.
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