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Parametric Production Planning

Author

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  • Curtis H. Jones

    (Harvard University Graduate School of Business Administration)

Abstract

This paper proposes a heuristic approach to the determination of work force and production levels. The existence of two feed-back rules (one for work force and one for production) is postulated. The universe of possible parameters is searched to find the set of parameters that provides the lowest cost or highest profit for a particular firm. Each set of parameters is evaluated by comparing the costs or profits resulting from the application of rules bearing these parameter values to a likely sequence of sales forecasts and actual sales. Decision rules formed in this way give cost and profit results nearly equal to those resulting from the application of the optimal techniques to purely mathematical problems. In more complex and more realistic situations, the results obtained by Parametric Production Planning may be superior to those achieved by a linear programming approach or a linear decision rule.

Suggested Citation

  • Curtis H. Jones, 1967. "Parametric Production Planning," Management Science, INFORMS, vol. 13(11), pages 843-866, July.
    • Handle: RePEc:inm:ormnsc:v:13:y:1967:i:11:p:843-866
    DOI: 10.1287/mnsc.13.11.843
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    Cited by:

    1. Wu, Chia-Chin & Chang, Ni-Bin, 2004. "Corporate optimal production planning with varying environmental costs: A grey compromise programming approach," European Journal of Operational Research, Elsevier, vol. 155(1), pages 68-95, May.
    2. Shih-Pin Chen & Wen-Lung Huang, 2014. "Solving Fuzzy Multiproduct Aggregate Production Planning Problems Based on Extension Principle," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 2014, pages 1-18, August.
    3. Buxey, Geoff, 2003. "Strategy not tactics drives aggregate planning," International Journal of Production Economics, Elsevier, vol. 85(3), pages 331-346, September.
    4. Gomes da Silva, Carlos & Figueira, José & Lisboa, João & Barman, Samir, 2006. "An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming," Omega, Elsevier, vol. 34(2), pages 167-177, April.
    5. Wang, Reay-Chen & Liang, Tien-Fu, 2005. "Applying possibilistic linear programming to aggregate production planning," International Journal of Production Economics, Elsevier, vol. 98(3), pages 328-341, December.

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