Optimal water allocation using a multi-objective evolutionary algorithm
Masters Thesis
Title | Optimal water allocation using a multi-objective evolutionary algorithm |
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Type | Masters Thesis |
Authors | |
Author | Ullah, G. M. Wali |
Supervisor | Langlands, Trevor |
Addie, Ron | |
Institution of Origin | University of Southern Queensland |
Qualification Name | Master of Science (Research) |
Number of Pages | 162 |
Year | 2020 |
Digital Object Identifier (DOI) | https://doi.org/10.26192/04p7-fp29 |
Abstract | Agriculture water management in Bangladesh has become a subject of increasing attention due to population growth. Therefore, it is necessary that we optimize water use in order to increase the agricultural production with The research engages with the optimum allocation of water in the agricultural sector of Bangladesh. We model the problem using multi-objective constrained optimization problem. The objectives in this problem are to maximize net return and minimizing deficit in environmental flow. A Non-Dominating Sorting Genetic Algorithm, NSGA-II, is used to solve the problem in this research to find the optimum result. The research indicates that the crops which are produced more and are more profitable in trade should be cultivated more as recommended by the model. The model predictions indicate that rainfall impacts on net return and environmental flow deficit more than water inflow under the scenarios in the Muhuri Irrigation Project (MIP) considered. |
Keywords | Muhuri Irrigation Project, net return, environmental flow deficit, multi-objective optimization problem, evolutionary algorithm, NSGAII |
ANZSRC Field of Research 2020 | 490108. Operations research |
Byline Affiliations | School of Sciences |
https://research.usq.edu.au/item/q5yy9/optimal-water-allocation-using-a-multi-objective-evolutionary-algorithm
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