International Journal of Sustainable Development Research
Volume 6, Issue 4, December 2020, Pages: 49-54
Received: Nov. 3, 2020;
Accepted: Dec. 3, 2020;
Published: Dec. 16, 2020
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Adane Akate, Department of Mathematics, Natural and Computational Science, Mekdela Amba University, Dessise, Ethiopia
In this paper we have studied the Dynamic programming problem and major area of applications of this approach has been introduced. Dynamic programming provides a means for determining optimal long-term crop management plans. However, most applications and their analysis on annual time steps with fixed strategies within the year, effectively ignoring conditional responses during the year. We suggest an alternative approach that captures the strategic responses within a cropping season to random weather variables as they unfold, reflecting farmers’ ability to adapt to weather realizations. Multistage decision problems a problem of dynamic programming problem there is numerically challenging. So for the analytical results, dynamic programming is able to obtain the optimal agricultural product problem, and also decides how many it consumes and how many it saves in material and permanently store in each period economically. However, in this study, the problem is considered deterministic in which all input parameters are constant. The objective is to find a sequence of actions (a so-called policy) that minimizes the total cost over the decision making horizon the purpose of this paper has been to introduce application of dynamic programming techniques by way of example. The end result of the model formulation reveals the applicability of dynamic programming in resolving long time of the problem.
Application of Dynamic Programing in Agriculture, Economics and Computer Science, International Journal of Sustainable Development Research.
Vol. 6, No. 4,
2020, pp. 49-54.
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