Application of Dynamic Programing in Agriculture, Economics and Computer Science

Adane Akate

doi:doi:10.11648/j.ijsdr.20200604.11

| Peer-Reviewed

Application of Dynamic Programing in Agriculture, Economics and Computer Science

Adane Akate

Published in International Journal of Sustainable Development Research (Volume 6, Issue 4)

Received: 3 November 2020 Accepted: 3 December 2020 Published: 16 December 2020

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

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.

Published in	International Journal of Sustainable Development Research (Volume 6, Issue 4)
DOI	10.11648/j.ijsdr.20200604.11
Page(s)	49-54
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

Dynamic Programming, Sub Problem, Stage, State

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.

Cite This Article

Plain Text BibTeX RIS

APA Style

Adane Akate. (2020). Application of Dynamic Programing in Agriculture, Economics and Computer Science. International Journal of Sustainable Development Research, 6(4), 49-54. https://doi.org/10.11648/j.ijsdr.20200604.11

Copy | Download

ACS Style

Adane Akate. Application of Dynamic Programing in Agriculture, Economics and Computer Science. Int. J. Sustain. Dev. Res. 2020, 6(4), 49-54. doi: 10.11648/j.ijsdr.20200604.11

Copy | Download

AMA Style

Adane Akate. Application of Dynamic Programing in Agriculture, Economics and Computer Science. Int J Sustain Dev Res. 2020;6(4):49-54. doi: 10.11648/j.ijsdr.20200604.11

Copy | Download

@article{10.11648/j.ijsdr.20200604.11,
  author = {Adane Akate},
  title = {Application of Dynamic Programing in Agriculture, Economics and Computer Science},
  journal = {International Journal of Sustainable Development Research},
  volume = {6},
  number = {4},
  pages = {49-54},
  doi = {10.11648/j.ijsdr.20200604.11},
  url = {https://doi.org/10.11648/j.ijsdr.20200604.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsdr.20200604.11},
  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.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - Application of Dynamic Programing in Agriculture, Economics and Computer Science
AU  - Adane Akate
Y1  - 2020/12/16
PY  - 2020
N1  - https://doi.org/10.11648/j.ijsdr.20200604.11
DO  - 10.11648/j.ijsdr.20200604.11
T2  - International Journal of Sustainable Development Research
JF  - International Journal of Sustainable Development Research
JO  - International Journal of Sustainable Development Research
SP  - 49
EP  - 54
PB  - Science Publishing Group
SN  - 2575-1832
UR  - https://doi.org/10.11648/j.ijsdr.20200604.11
AB  - 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.
VL  - 6
IS  - 4
ER  -

Copy | Download

Author Information

Adane Akate

Department of Mathematics, Natural and Computational Science, Mekdela Amba University, Dessise, Ethiopia

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Adane Akate. (2020). Application of Dynamic Programing in Agriculture, Economics and Computer Science. International Journal of Sustainable Development Research, 6(4), 49-54. https://doi.org/10.11648/j.ijsdr.20200604.11

Copy | Download

ACS Style

Adane Akate. Application of Dynamic Programing in Agriculture, Economics and Computer Science. Int. J. Sustain. Dev. Res. 2020, 6(4), 49-54. doi: 10.11648/j.ijsdr.20200604.11

Copy | Download

AMA Style

Adane Akate. Application of Dynamic Programing in Agriculture, Economics and Computer Science. Int J Sustain Dev Res. 2020;6(4):49-54. doi: 10.11648/j.ijsdr.20200604.11

Copy | Download

@article{10.11648/j.ijsdr.20200604.11,
  author = {Adane Akate},
  title = {Application of Dynamic Programing in Agriculture, Economics and Computer Science},
  journal = {International Journal of Sustainable Development Research},
  volume = {6},
  number = {4},
  pages = {49-54},
  doi = {10.11648/j.ijsdr.20200604.11},
  url = {https://doi.org/10.11648/j.ijsdr.20200604.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsdr.20200604.11},
  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.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - Application of Dynamic Programing in Agriculture, Economics and Computer Science
AU  - Adane Akate
Y1  - 2020/12/16
PY  - 2020
N1  - https://doi.org/10.11648/j.ijsdr.20200604.11
DO  - 10.11648/j.ijsdr.20200604.11
T2  - International Journal of Sustainable Development Research
JF  - International Journal of Sustainable Development Research
JO  - International Journal of Sustainable Development Research
SP  - 49
EP  - 54
PB  - Science Publishing Group
SN  - 2575-1832
UR  - https://doi.org/10.11648/j.ijsdr.20200604.11
AB  - 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.
VL  - 6
IS  - 4
ER  -

Copy | Download