An Empirical Application and Evaluation of Discrete Stochastic Programming in Farm Management

Discrete stochastic programming has been suggested as a means of solving sequential decision problems under uncertainty, but as yet little or no empirical evidence of the capabilities of this technique in solving such problems has appeared. This paper presents in some detail an empirical application of discrete stochastic programming, including a discussion of data requirements, matrix construction, and solution interpretation. Based on this empirical evidence, the problem‐solving potential of the technique is evaluated.