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Effective Information for Offline Stochastic Feedback and Optimal Control of Dynamic Systems

Author

Listed:
  • A. Herbon

    (College of Judea and Samaria)

  • E. Khmelnitsky

    (Tel-Aviv University)

  • F. Blanchini

    (University of Udine)

Abstract

The impact of uncertain future events on decision making in a stochastic environment is modeled in this paper. Such modeling is presented for both feedback and optimal control problems. This research overcomes the difficulties of forecasting that arise when considering future information. In this paper, we seek to find the minimum amount of information (effective information) necessary to evaluating system performance offline or to optimally control a system. The existence of effective information is proved and a methodology for determining it is developed. It is also shown that ignoring information beyond the planning horizon leads to significant performance loss and may even lead to violating the constraints of a control problem.

Suggested Citation

  • A. Herbon & E. Khmelnitsky & F. Blanchini, 2003. "Effective Information for Offline Stochastic Feedback and Optimal Control of Dynamic Systems," Journal of Optimization Theory and Applications, Springer, vol. 116(2), pages 283-310, February.
    • Handle: RePEc:spr:joptap:v:116:y:2003:i:2:d:10.1023_a:1022405904070
    DOI: 10.1023/A:1022405904070
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    References listed on IDEAS

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    1. Jain, Karuna & Silver, Edward A., 1994. "Lot sizing for a product subject to obsolescence or perishability," European Journal of Operational Research, Elsevier, vol. 75(2), pages 287-295, June.
    2. de Sousa, Jorge Freire & Guimaraes, Rui Campos, 1997. "Setting the length of the planning horizon in the vehicle replacement problem," European Journal of Operational Research, Elsevier, vol. 101(3), pages 550-559, September.
    3. Neck, Reinhard, 1984. "Stochastic control theory and operational research," European Journal of Operational Research, Elsevier, vol. 17(3), pages 283-301, September.
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