Stochastic Dynamic Programming

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Stochastic Dynamic Programming (SDP) and its deterministic counterpart, Dynamic Programming (DP), describe techniques used to solve a class of constrained optimization problems in which decision-making today affects the stock of a resource and decision-making in future periods.

Helpful examples of the use of DP or SDP modeling techniques can be found in the following papers:

  • Bryant, K.J., J.W. Mjelde, and R.D. Lacewell. 1993. An intraseasonal dynamic optimization model to allocate irrigation water between crops. American Journal of Agricultural Economics, 75:1021-1029.
  • Cobourn, K.M., R.E. Goodhue, and J.C. Williams. 2013. Managing a pest with harvest timing: implications for crop quality and price. European Review of Agricultural Economics, 40:761-784.
  • Livingston, M., M.J. Roberts, and Y. Zhang. 2015. Optimal sequential plantings of corn and soybeans under price uncertainty. American Journal of Agricultural Economics, 97:855-878.

Project team members can access these papers in the project Dropbox folder (directory: Model Integration > Model papers > SDP).