Modeling of a cereal-livestock production system in Karak, Jordan: A dynamic stochastic programming approach
Agricultural production decisions are rooted in the balance of managing finite resources levels with the needs of the household. Modeling the agricultural system to meet this needs of the household and ensure the optimal extraction of resources over time presents computational challenges due to size. The research presents the mathematical issues with solving long horizon dynamic stochastic models, and presents a two-step procedure for approximating solutions based on the principles of Lagrangian optimization. This dissertation models a typical agricultural household in Karak, Jordan that consists of an integrated cereal and livestock production system. In the first step a crop model is solved using dynamic programming to evaluate the trade-offs of decisions over an infinite horizon, with attention towards valuations of soil attributes. In the second step of the model, a one year discrete stochastic program is developed to reflect the decision making of an integrated crop and livestock household that optimizes their choices of risky outcomes during the year, as well as evaluates future years through the terminal values of soil solved in the first step. In both steps of the model, a new approach is presented for integrating biological simulation results to define stochastic process and outcomes of agriculture through a system that is economically rigorous.
Preckel, Purdue University.
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