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A Chance-Constrained Model for Real-Time Control in Research and Development Management

Author

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  • A. Charnes

    (Northwestern University)

  • A. C. Stedry

    (Carnegie Institute of Technology)

Abstract

Funding of research projects is considered as encompassing three stages: (1) an initial short run plan for funding based upon projected regular demands and availability subject to random deviations; (2) adjustment of the initial plan to take into account the actual regular demands and availability and the funding of significant break-throughs which occur at random intervals preempting other demands; and (3) a plan for longer-run availability and demands which constitute a "posture" desired subsequent to the funding adjustments of (2). The essence of the distribution of the unexpected demands is multi-modality with low probability of occurrence but high resource demand when they do occur. This approach represents a substantial departure from the usual planning model development which produces only an optimal plan based on forecasted developments without provision for adjustment when the forecasted events actually materialize and additional unexpected demands are placed on resources. The adjustment process explored here--which provides the mechanism for optimal implementation of the original plan or control of resource allocation-enables optimal response to information received in "real-time" avoiding the frequently observed over- or under-response to receipt of such information without reference to the impact of the interim decision on future capabilities.

Suggested Citation

  • A. Charnes & A. C. Stedry, 1966. "A Chance-Constrained Model for Real-Time Control in Research and Development Management," Management Science, INFORMS, vol. 12(8), pages 353-362, April.
  • Handle: RePEc:inm:ormnsc:v:12:y:1966:i:8:p:b353-b362
    DOI: 10.1287/mnsc.12.8.B353
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    Cited by:

    1. Roy Cerqueti & Daniele Marazzina & Marco Ventura, 2016. "Optimal Investment in Research and Development Under Uncertainty," Journal of Optimization Theory and Applications, Springer, vol. 168(1), pages 296-309, January.
    2. Pelin G. Canbolat & Boaz Golany & Inbal Mund & Uriel G. Rothblum, 2012. "A Stochastic Competitive R&D Race Where “Winner Takes All”," Operations Research, INFORMS, vol. 60(3), pages 700-715, June.

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