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Product Cycling With Uncertain Yields: Analysis and Application to the Process Industry

Author

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  • Kumar Rajaram

    (Decision, Operations, and Technology Management, The Anderson School, University of California at Los Angeles, 110 Westwood Plaza, Los Angeles, California 90095--1481)

  • Uday S. Karmarkar

    (Decision, Operations, and Technology Management, The Anderson School, University of California at Los Angeles, 110 Westwood Plaza, Los Angeles, California 90095--1481)

Abstract

We formulate the dynamic product-cycling problem with yield uncertainty and buffer limits to determine how much product to produce at what time to minimize total expected switching, production, inventory storage, and backorder costs. A “restricted” Lagrangian technique is used to develop a lower bound and a model-based Lagrangian heuristic. We also develop an operational heuristic and a greedy heuristic. The operational heuristic has been implemented at seven refineries at Cerestar, Europe's leading manufacturer of wheat-and corn-based starch products in the food-processing industry . This has already reduced total costs by around 5 percent or $3 million annually at these sites. Tests of the Lagrangian heuristic on data from these refineries during this period have shown the potential to further reduce total costs by at least 2 percent or about $1 million. In addition, the Lagrangian heuristic has provided an objective basis to evaluate the economic impact of several strategic decisions involving issues such as buffer expansion, variability reduction, and product selection.

Suggested Citation

  • Kumar Rajaram & Uday S. Karmarkar, 2002. "Product Cycling With Uncertain Yields: Analysis and Application to the Process Industry," Operations Research, INFORMS, vol. 50(4), pages 680-691, August.
    • Handle: RePEc:inm:oropre:v:50:y:2002:i:4:p:680-691
    DOI: 10.1287/opre.50.4.680.2867
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    References listed on IDEAS

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    Cited by:

    1. G. P. Kiesmüller & K. Inderfurth, 2018. "Approaches for periodic inventory control under random production yield and fixed setup cost," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(2), pages 449-477, March.
    2. Qing Li & Shaohui Zheng, 2006. "Joint Inventory Replenishment and Pricing Control for Systems with Uncertain Yield and Demand," Operations Research, INFORMS, vol. 54(4), pages 696-705, August.
    3. Tinglong Dai & Kinshuk Jerath, 2019. "Salesforce Contracting Under Uncertain Demand and Supply: Double Moral Hazard and Optimality of Smooth Contracts," Marketing Science, INFORMS, vol. 38(5), pages 852-870, September.
    4. Van Nieuwenhuyse, Inneke & Vandaele, Nico & Rajaram, Kumar & Karmarkar, Uday S., 2007. "Buffer sizing in multi-product multi-reactor batch processes: Impact of allocation and campaign sizing policies," European Journal of Operational Research, Elsevier, vol. 179(2), pages 424-443, June.
    5. Diwakar Gupta & William L. Cooper, 2005. "Stochastic Comparisons in Production Yield Management," Operations Research, INFORMS, vol. 53(2), pages 377-384, April.
    6. Rajaram, Kumar & Robotis, Andreas, 2004. "Analyzing variability in continuous processes," European Journal of Operational Research, Elsevier, vol. 156(2), pages 312-325, July.
    7. Burak Kazaz & Scott Webster, 2011. "The Impact of Yield-Dependent Trading Costs on Pricing and Production Planning Under Supply Uncertainty," Manufacturing & Service Operations Management, INFORMS, vol. 13(3), pages 404-417, July.
    8. Victor F. Araman & Ioana Popescu, 2010. "Media Revenue Management with Audience Uncertainty: Balancing Upfront and Spot Market Sales," Manufacturing & Service Operations Management, INFORMS, vol. 12(2), pages 190-212, December.
    9. Kumar Rajaram & Uday S. Karmarkar, 2004. "Campaign Planning and Scheduling for Multiproduct Batch Operations with Applications to the Food-Processing Industry," Manufacturing & Service Operations Management, INFORMS, vol. 6(3), pages 253-269, October.
    10. Zhong, Yuanguang & Liu, Ju & Zhou, Yong-Wu & Cao, Bin & Cheng, T.C. Edwin, 2022. "Robust contract design and coordination under consignment contracts with revenue sharing," International Journal of Production Economics, Elsevier, vol. 253(C).
    11. Kaijie Zhu & Rachel Q. Zhang & Fugee Tsung, 2007. "Pushing Quality Improvement Along Supply Chains," Management Science, INFORMS, vol. 53(3), pages 421-436, March.
    12. Felipe Caro & Kumar Rajaram & Jens Wollenweber, 2012. "Process Location and Product Distribution with Uncertain Yields," Operations Research, INFORMS, vol. 60(5), pages 1050-1063, October.
    13. Hossein Jahandideh & Kumar Rajaram & Kevin McCardle, 2020. "Production Campaign Planning Under Learning and Decay," Manufacturing & Service Operations Management, INFORMS, vol. 22(3), pages 615-632, May.
    14. Mili Mehrotra & Milind Dawande & Srinagesh Gavirneni & Mehmet Demirci & Sridhar Tayur, 2011. "OR PRACTICE---Production Planning with Patterns: A Problem from Processed Food Manufacturing," Operations Research, INFORMS, vol. 59(2), pages 267-282, April.

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