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Quantity and Due Date Quoting Available to Promise

Author

Listed:
  • Chien-Yu Chen

    (University of Maryland)

  • Zhen-Ying Zhao

    (University of Maryland)

  • Michael O. Ball

    (University of Maryland)

Abstract

The available to promise (ATP) function has increasingly attracted the attention of the supply chain management research community as a tool for enhancing the responsiveness of order promising and the reliability of order fulfillment. It directly links available resources, including both material and capacity, with customer orders and, thus, affects the overall performance of a supply chain. In this paper, a mixed integer programming (MIP) model for a quantity and due date quoting ATP mechanism is presented. This model can provide individual order delivery dates for a batch of customer orders that arrive within a predefined batching interval. In addition, the model allows customized configurations and takes into account a variety of realistic supply chain constraints, such as material compatibility, substitution preferences, capacity utilization, and material reserve. We conclude this paper with sensitivity analysis of performance impacts with respect to batching interval size and material reserve policy.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:infosf:v:3:y:2001:i:4:d:10.1023_a:1012837207691
    DOI: 10.1023/A:1012837207691
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    Citations

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    Cited by:

    1. Chiang, David Ming-Huang & Wu, Andy Wei-Di, 2011. "Discrete-order admission ATP model with joint effect of margin and order size in a MTO environment," International Journal of Production Economics, Elsevier, vol. 133(2), pages 761-775, October.
    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. Afshin Mansouri, S. & Gallear, David & Askariazad, Mohammad H., 2012. "Decision support for build-to-order supply chain management through multiobjective optimization," International Journal of Production Economics, Elsevier, vol. 135(1), pages 24-36.
    4. 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.
    5. Tsai, Kune-muh & Wang, Shan-chi, 2009. "Multi-site available-to-promise modeling for assemble-to-order manufacturing: An illustration on TFT-LCD manufacturing," International Journal of Production Economics, Elsevier, vol. 117(1), pages 174-184, January.
    6. Venkatadri, Uday & Srinivasan, Ashok & Montreuil, Benoit & Saraswat, Ashish, 2006. "Optimization-based decision support for order promising in supply chain networks," International Journal of Production Economics, Elsevier, vol. 103(1), pages 117-130, September.
    7. Raul Oltra-Badenes & Hermenegildo Gil-Gomez & Jose M Merigo & Daniel Palacios-Marques, 2019. "Methodology and model-based DSS to managing the reallocation of inventory to orders in LHP situations. Application to the ceramics sector," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-19, July.
    8. Alarcón, F. & Alemany, M.M.E. & Ortiz, A., 2009. "Conceptual framework for the characterization of the order promising process in a collaborative selling network context," International Journal of Production Economics, Elsevier, vol. 120(1), pages 100-114, July.
    9. 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.
    10. Alexander Seitz & Hans Ehm & Renzo Akkerman & Sarah Osman, 2016. "A robust supply chain planning framework for revenue management in the semiconductor industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(6), pages 523-533, December.
    11. Volling, Thomas & Spengler, Thomas S., 2011. "Modeling and simulation of order-driven planning policies in build-to-order automobile production," International Journal of Production Economics, Elsevier, vol. 131(1), pages 183-193, May.
    12. Quante, R. & Fleischmann, M. & Meyr, H., 2009. "A Stochastic Dynamic Programming Approach to Revenue Management in a Make-to-Stock Production System," ERIM Report Series Research in Management ERS-2009-015-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    13. Uday Venkatadri & Shentao Wang & Ashok Srinivasan, 2021. "A Model for Demand Planning in Supply Chains with Congestion Effects," Logistics, MDPI, vol. 5(1), pages 1-24, January.
    14. Thammakoranonta, Nithinant & Radhakrishnan, Abirami & Davis, Steve & Peck, John C. & Miller, Janis L., 2008. "A protocol for the order commitment decision in a supply network," International Journal of Production Economics, Elsevier, vol. 115(2), pages 515-527, October.

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