Volume 5, Issue 4, December 2019, Page: 73-82
A Comparative Study on Harvesting Plan Predicting Insurance with Two-Stage Stochastic Analysis
Hashnayne Ahmed, Department of Mathematics, Faculty of Science and Engineering, University of Barishal, Barishal, Bangladesh
Shek Ahmed, Department of Mathematics, Faculty of Science and Engineering, University of Barishal, Barishal, Bangladesh
Received: Dec. 9, 2019;       Accepted: Dec. 20, 2019;       Published: Dec. 31, 2019
DOI: 10.11648/j.ijdst.20190504.12      View  381      Downloads  89
Abstract
The exception of considering uncertainty could be very detrimental to the outcomes of any systems or phenomena in the long run. Stochastic Process describes the way of considering uncertainty in different sectors of our life. We use Linear Programming for planning at its best. It is also considered as the best optimization technique for taking decisions or planning. But this planning tool disappoints us in optimization for unexpected risk or stochasticity. Consideration of stochasticity for a farmer to devote land on different crops for harvesting could be some insurance for the farmer with the best possible outcomes. Stochastic Programming studies these types of optimization techniques with risk consideration for better decisions in every step of our life. In this paper, we described the early starting of uncertainty calculation or stochastic approach and the evolution of stochastic optimization fields. Stochastic optimization is rather important in the sense of uncertainty calculation than sensitivity analysis and works through data gained from experience. We also present a stochastic model with some uncertainty issues in harvesting to make better outcomes. Some application areas are also discussed.
Keywords
Stochastic Optimization, Stochastic Programming, Stochastic Modeling, Uncertainty Calculation, LINDO
To cite this article
Hashnayne Ahmed, Shek Ahmed, A Comparative Study on Harvesting Plan Predicting Insurance with Two-Stage Stochastic Analysis, International Journal on Data Science and Technology. Vol. 5, No. 4, 2019, pp. 73-82. doi: 10.11648/j.ijdst.20190504.12
Copyright
Copyright © 2019 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.
Reference
[1]
Birge, John R., and Francois Louveaux. Introduction to stochastic programming. Springer Science & Business Media, 2011.
[2]
Kall, Peter, and Janos Mayer. Stochastic linear programming. Vol. 7. Berlin: Springer-Verlag, 1976.
[3]
Wallace, Stein W., and William T. Ziemba, eds. Applications of stochastic programming. Society for Industrial and Applied Mathematics, 2005.
[4]
Ahmed, Hashnayne. "Graph Routing Problem Using Euler’s Theorem and Its Applications." (2019).
[5]
Dantzig, George B. "Linear programming under uncertainty." Stochastic programming. Springer, New York, NY, 2010. 1-11.
[6]
Sen, Suvrajeet, and Julia L. Higle. "An introductory tutorial on stochastic linear programming models." Interfaces 29.2 (1999): 33-61.
[7]
Tintner, Gerhard. "A note on stochastic linear programming." Econometrica: Journal of the Econometric Society (1960): 490-495.
[8]
Molla, Md Hasib Uddin, and M. Babul Hasan. "Art of Formulating LPs and IPs from Real Life Problems." Dhaka University Journal of Science 61.2 (2013): 185-191.
[9]
Spall, James C. "Simultaneous perturbation stochastic approximation." Introduction to stochastic search and optimization: Estimation, simulation, and control (2003): 176-207.
[10]
Doob, Joseph Leo. Stochastic processes. Vol. 101. Wiley: New York, 1953.
[11]
Kumar, Panqanamala Ramana, and Pravin Varaiya. Stochastic systems: Estimation, identification, and adaptive control. Vol. 75. SIAM, 2015.
[12]
Ghaffari-Hadigheh, Alireza, and Zeinab Zarea. "One-Stage Uncertain Linear optimization." Journal of Hyperstructures 7.1 (2019).
[13]
King, Alan J., and Stein W. Wallace. Modeling with stochastic programming. Springer Science & Business Media, 2012.
[14]
Inc, Lindo Systems. "LINDO User's Manuals." LINDO Systems, Inc (2003).
[15]
Wu, Hao-Hsiang, and Simge Küçükyavuz. "A two-stage stochastic programming approach for influence maximization in social networks." Computational Optimization and Applications 69.3 (2018): 563-595.
[16]
Ameri, Mahmoud, et al. "A Two-Stage Stochastic Model for Maintenance and Rehabilitation Planning of Pavements." Mathematical Problems in Engineering, 2019.
[17]
Xu, Ye, et al. "Stochastic optimization model for water allocation on a watershed scale considering wetland’s ecological water requirement." Ecological Indicators 92 (2018): 330-341.
[18]
Bertsimas, Dimitris, and Nataly Youssef. "Stochastic optimization in supply chain networks: averaging robust solutions." Optimization Letters (2019): 1-17.
[19]
Gassmann, Horand I., et al. "Introduction to stochastic programming applications." Applications of stochastic programming. Society for Industrial and Applied Mathematics, 2005. 179-184.
[20]
Sultan, Alan. Linear programming: An introduction with applications. Elsevier, 2014.
[21]
Ahmed, Hashnayne. "Formulation of Two-Stage Stochastic Programming with Fixed Recourse." Britain International of Exact Sciences (BIoEx) Journal 1.1 (2019): 18-21.
[22]
Ahmed, Hashnayne. “A Proposed Linear Programming Based Algorithm to solve Arc Routing Problems.” International Journal of Mathematical Sciences and Computing 6.1 (2020).
Browse journals by subject