Abstract
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.
Highlights
The term dynamic programming was originally used in the1940s by Richard Ernest Bellman to describe the process of solving problems where one needs to find the best decisions one after another [1, 12]
Applications of dynamic programming there are many areas where we can find the optimal solution of the problem using dynamic programming are bioinformatics, control theory, information theory, operations research, agriculture, economics and many applications of computer science like artificial intelligence graphics [7, 13]
Dynamic programming is applicable in economics, because it decides how many it consumes and how many it save in material and permanently store in each period
Summary
1940s by Richard Ernest Bellman to describe the process of solving problems where one needs to find the best decisions one after another [1, 12]. Dynamic programming is used to solve the multistage optimization problem in which dynamic means reference to time and programming means planning or tabulation [15]. It refers to a computational method involving recurrence relations. Agriculture is mostly dominated by smallholders, farmers One of their main problems is how to utilize their products most effectively so that they can gain more income. Introduced and studied properties of solutions for functional equations arising in dynamic programming of multistage decision processes [10]. A dynamic program, we seek to find a state-dependent rule for choosing which action to take (a policy) that minimizes the expected total cost incurred
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Sustainable Development Research
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
