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Multiobjective Production Planning at LG Display

Author

Listed:
  • Moo-Sung Sohn

    (School of Industrial Management Engineering, Korea University, Seoul, South Korea, 02841; Process Innovation Group, LG Display Co., Ltd., Kyeonggi-do, South Korea, 10845)

  • Jiwoong Choi

    (Gurobi Korea Co., Ltd., Seoul, South Korea, 06775)

  • Hoseog Kang

    (Process Innovation Group, LG Display Co., Ltd., Kyeonggi-do, South Korea, 10845)

  • In-Chan Choi

    (School of Industrial Management Engineering, Korea University, Seoul, South Korea, 02841)

Abstract

In this paper, we address a glass-cutting process, which we call a post-cell process, for production planning at LG Display, one of the leading display-panel manufacturing companies in Korea. This process involves cutting glass into a variety of panels of different sizes to meet customer demands. We present mixed-integer programming models and a solution approach to generate production plans for the post-cell process. In the models, we consider multiple goals, such as minimization of shortage, inventory, and item changeover. In our solution approach, the goals are prioritized based on their importance and treated sequentially to meet the solution time requirements as set forth by work-site planners. The results of our computational experiments with real-world problem instances at LG Display show that our approach provides significant benefits in operational efficiency.

Suggested Citation

  • Moo-Sung Sohn & Jiwoong Choi & Hoseog Kang & In-Chan Choi, 2017. "Multiobjective Production Planning at LG Display," Interfaces, INFORMS, vol. 47(4), pages 279-291, August.
    • Handle: RePEc:inm:orinte:v:47:y:2017:i:4:p:279-291
    DOI: 10.1287/inte.2017.0891
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    References listed on IDEAS

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    1. Jennifer L. Loveland & Susan K. Monkman & Douglas J. Morrice, 2007. "Dell Uses a New Production-Scheduling Algorithm to Accommodate Increased Product Variety," Interfaces, INFORMS, vol. 37(3), pages 209-219, June.
    2. Christodoulos Floudas & Xiaoxia Lin, 2005. "Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications," Annals of Operations Research, Springer, vol. 139(1), pages 131-162, October.
    3. Wolsey, Laurence A., 1997. "MIP modelling of changeovers in production planning and scheduling problems," European Journal of Operational Research, Elsevier, vol. 99(1), pages 154-165, May.
    4. Andrew J. Miller & Laurence A. Wolsey, 2003. "Tight Mip Formulation for Multi-Item Discrete Lot-Sizing Problems," Operations Research, INFORMS, vol. 51(4), pages 557-565, August.
    5. Gaetan Belvaux & Laurence A. Wolsey, 2001. "Modelling Practical Lot-Sizing Problems as Mixed-Integer Programs," Management Science, INFORMS, vol. 47(7), pages 993-1007, July.
    6. Chan, Felix T. S. & Chung, S. H. & Wadhwa, Subhash, 2005. "A hybrid genetic algorithm for production and distribution," Omega, Elsevier, vol. 33(4), pages 345-355, August.
    7. Seokcheol Chang & Jaewoo Chung, 2013. "Optimization Models for Production Planning in LG Display," Interfaces, INFORMS, vol. 43(6), pages 518-529, December.
    8. BELVAUX, Gaetan & WOLSEY, Laurence A., 2001. "Modelling practical lot-sizing problems as mixed-integer programs," LIDAM Reprints CORE 1516, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Wolsey, L. A., 1997. "MIP modelling of changeovers in production planning and scheduling problems," LIDAM Reprints CORE 1271, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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