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Scheduling Solutions for the Paper Industry

Author

Listed:
  • Pinar Keskinocak

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Frederick Wu

    (IBM T. J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598)

  • Richard Goodwin

    (IBM T. J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598)

  • Sesh Murthy

    (IBM T. J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598)

  • Rama Akkiraju

    (IBM T. J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598)

  • Santhosh Kumaran

    (IBM Supply Chain Optimization Development, 3200 Windy Hill Road, Atlanta, Georgia 30339)

  • Annap Derebail

    (IBM Supply Chain Optimization Development, 3200 Windy Hill Road, Atlanta, Georgia 30339)

Abstract

This paper describes a decision support system for paper production scheduling. This is the first system to provide an integrated solution to paper production scheduling and to consider interactions between different stages of the manufacturing and distribution process. Using a multicriteria optimization approach, the system generates multiple enterprisewide schedules to reveal tradeoffs between the multiple, often competing, objectives. The large portfolio of algorithms used by the system is embedded in an agent-based decision support framework, called Asynchronous Team (A-Team). Successful implementations of the system in several paper mills in North America have resulted in significant savings and improved customer satisfaction.

Suggested Citation

  • Pinar Keskinocak & Frederick Wu & Richard Goodwin & Sesh Murthy & Rama Akkiraju & Santhosh Kumaran & Annap Derebail, 2002. "Scheduling Solutions for the Paper Industry," Operations Research, INFORMS, vol. 50(2), pages 249-259, April.
    • Handle: RePEc:inm:oropre:v:50:y:2002:i:2:p:249-259
    DOI: 10.1287/opre.50.2.249.425
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    References listed on IDEAS

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    Cited by:

    1. Amanda O. C. Ayres & Betania S. C. Campello & Washington A. Oliveira & Carla T. L. S. Ghidini, 2021. "A Bi-Integrated Model for coupling lot-sizing and cutting-stock problems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 1047-1076, December.
    2. Erjavec, J. & Gradisar, M. & Trkman, P., 2012. "Assessment of stock size to minimize cutting stock production costs," International Journal of Production Economics, Elsevier, vol. 135(1), pages 170-176.
    3. Florian Jaehn & Raisa Juopperi, 2019. "A Description of Supply Chain Planning Problems in the Paper Industry with Literature Review," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(01), pages 1-39, February.
    4. Casey Chung & Milind Dawande & Divakar Rajamani & Chelliah Sriskandarajah, 2011. "A Short-Range Scheduling Model for Blockbuster's Order-Processing Operation," Interfaces, INFORMS, vol. 41(5), pages 466-484, October.
    5. Xiaoqiang Cai & Xianyi Wu & Xian Zhou, 2021. "Optimal unrestricted dynamic stochastic scheduling with partial losses of work due to breakdowns," Annals of Operations Research, Springer, vol. 298(1), pages 43-64, March.
    6. Constantine Goulimis & Gaston Simone, 2020. "Reel Stock Analysis for an Integrated Paper Packaging Company," Papers 2011.05858, arXiv.org, revised Nov 2020.
    7. Sanjay L. Ahire & Michael F. Gorman & David Dwiggins & Oleh Mudry, 2007. "Operations Research Helps Reshape Operations Strategy at Standard Register Company," Interfaces, INFORMS, vol. 37(6), pages 553-565, December.
    8. Flisberg, Patrik & Nilsson, Stefan & Rönnqvist, Mikael, 2007. "Optimized on-line process control of bleaching operations with OptCab," Discussion Papers 2007/9, Norwegian School of Economics, Department of Business and Management Science.

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