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Simulation Tests of Lot Size Programming

Author

Listed:
  • B. P. Dzielinski

    (International Business Machines Corporation, Yorktown Heights, New York)

  • C. T. Baker

    (International Business Machines Corporation, Yorktown Heights, New York)

  • A. S. Manne

    (International Business Machines Corporation, Yorktown Heights, New York)

Abstract

This paper presents the results of some digital computer simulation tests of a procedure for the economic planning of lot sizes, work force, and inventories. A dynamic, deterministic, linear programming model was used to obtain approximate solutions to the actual problem which is both dynamic and stochastic. The tests were made with data taken from an actual factory. An alternate procedure, based upon single-item inventory control, was also tested; its results were compared with those obtained from the linear programming model. On the basis of these tests, this linear programming method appears to offer a promising method for the practical economic planning of production activities.

Suggested Citation

  • B. P. Dzielinski & C. T. Baker & A. S. Manne, 1963. "Simulation Tests of Lot Size Programming," Management Science, INFORMS, vol. 9(2), pages 229-258, January.
    • Handle: RePEc:inm:ormnsc:v:9:y:1963:i:2:p:229-258
    DOI: 10.1287/mnsc.9.2.229
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    Citations

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    Cited by:

    1. Jans, R.F. & Degraeve, Z., 2005. "Modeling Industrial Lot Sizing Problems: A Review," ERIM Report Series Research in Management ERS-2005-049-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.
    2. Hax, Arnoldo C. & Meal, Harlan C., 1973. "Hierarchical integration of production planning and scheduling," Working papers 656-73., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    3. Joachim Arts & Simme Flapper, 2015. "Aggregate overhaul and supply chain planning for rotables," Annals of Operations Research, Springer, vol. 224(1), pages 77-100, January.

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