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The present study deals with the application of Genetic Algorithms (GA) for irrigation planning. The GA technique is used to evolve optimum cropping pattern for maximizing net benefits for the case study of Jayakwadi Irrigation project, Maharashtra, India. Constraints include continuity equation, land and water requirements, crop diversification, storage and canal capacity etc. Penalty function approach is used to convert constrained problem into an unconstrained one. For fixing GA parameters the model is run for three selection functions, three cross over operators, four mutations for population size of 50 and generations 200. It is observed that combination of tournament selection, simple cross over and boundary mutation is found to be suitable. |
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