Optimal water allocation using a multi-objective evolutionary algorithm
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 increasing needs of the population as well as to fulfil the need for a sound economy of the country as a whole.

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.