Please enter verification code
Confirm
Application of Dynamic Programing in Agriculture, Economics and Computer Science
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
Views 69      Downloads 22
Author
Adane Akate, Department of Mathematics, Natural and Computational Science, Mekdela Amba University, Dessise, Ethiopia
Article Tools
Follow on us
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.
Keywords
Dynamic Programming, Sub Problem, Stage, State
To cite this article
Adane Akate, Application of Dynamic Programing in Agriculture, Economics and Computer Science, International Journal of Sustainable Development Research. Vol. 6, No. 4, 2020, pp. 49-54. doi: 10.11648/j.ijsdr.20200604.11
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
Adda, J., Cooper, R. and Cooper, R. W., 2003. Dynamic economics: quantitative methods and applications. MIT press.
[2]
Beaumont, N., 2010. Using dynamic programming to determine an optimal strategy in a contract bridge tournament. Journal of the Operational Research Society, 61 (5), pp. 732-739.
[3]
Biswajit B. 2010. Dynamic Programming – Its Principles, Applications, Strengths, And Limitations, international Journal of Engineering Science and Technology Vol. 2 (9), 4822-4826.
[4]
El Karoui, N. and Quenez, M. C., 1995. Dynamic programming and pricing of contingent claims in an incomplete market. SIAM journal on Control and Optimization, 33 (1), pp. 29-66.
[5]
Gerard C., Reha T 2006. Optimization Methods in Finance, Carnegie Mellon University, Pittsburgh, PA 15213 USA.
[6]
Hamdy. A. Taha, (2006), “Operations Research; An Introduction”, 8th edition, prentice – hall of India private limited, New Delhi.
[7]
Herbert S. Wilf, Algorithms and Complexity, University of Pennsylvania, Internet Edition, Summer, 1994.
[8]
J. N. Tsitsiklis and B. Van Roy, "Optimal Stopping of Markov Processes: Hilbert Space Theory, Approximation Algorithms, and an Application to Pricing Financial Derivatives", IEEE Transactions on Automatic Control; Vol. 44, No. 10, October 1999, pp. 18401851.
[9]
Liu, Z. and Kang, S. M., 2006. Properties of solutions for certain functional equations arising in dynamic programming. Journal of Global Optimization, 34 (2), pp. 273-292.
[10]
Professor Bergin, “Lecture Notes on Dynamic Programming”, Economics 200E, Spring 1998.
[11]
Sarttra, T., Manokuakoon, S., Horadee, S. and Choosakulwong, K., 2013. Application of dynamic programming to agricultural land allocation: case study Phutthamonthon District, Nakhon Pathom Province, Thailand. In Proceedings of the International MultiConference of Engineers and Computer Scientists (Vol. 2).
[12]
Slater L. J. (1964) A dynamic programming process, journal on dynamic programming in the computer, volume 7, pp 36-39.
[13]
S. Dasgupta, C. H. Papadimitriou, and U. V. Vazirani, “Algorithms”, TMGH, 5th reprint, 2009.
[14]
Parsons, D. J. et al., 2009: Weed Manager – A model based decision support system for weed management in arable crops, Computers and electronics in agriculture, 65, pp. 155–167. SEPPELT, R., VOINOV, A., 2002.
[15]
Bellman, R., 1957: Dynamic programming. The Princeton University Press, Princeton, NJ.
[16]
Janova, J. 2010. The dynamic programming approach to long term production planning in agriculture. Acta univ. agric. et silvic. Mendel. Brun., 2011, LIX, No. 2, pp. 129–136.
ADDRESS
Science Publishing Group
1 Rockefeller Plaza,
10th and 11th Floors,
New York, NY 10020
U.S.A.
Tel: (001)347-983-5186