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Irrigation planning using Genetic Algorithms

The present study deals with the application of Genetic Algorithms(GA) for irrigation planning. The GA technique is used to evolve efficient cropping pattern for maximizing benefits for an irrigation project in India. Constraints include continuity equation, land and water requirements, crop diversi...

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Published in:Water resources management 2004-04, Vol.18 (2), p.163-176
Main Authors: Raju, K.S, Kumar, D.N
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description The present study deals with the application of Genetic Algorithms(GA) for irrigation planning. The GA technique is used to evolve efficient cropping pattern for maximizing benefits for an irrigation project in India. Constraints include continuity equation, land and water requirements, crop diversification and restrictions on storage. Penalty function approach is used to convert constrained problem into an unconstrained one. For fixing GA parameters the model is run for various values of population, generations, cross over and mutation probabilities. It is found that the appropriate parameters for number of generations, population size, crossover probability, and mutation probability are 200, 50, 0.6 and 0.01 respectively for the present study. Results obtained by GA are compared with Linear Programming solution and found to be reasonably close. GA is found to be an effective optimization tool for irrigation planning and the results obtained can be utilized for efficient planning of any irrigation system.[PUBLICATION ABSTRACT]
doi_str_mv 10.1023/B:WARM.0000024738.72486.b2
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subjects Algorithms
Crop diversification
Cropping systems
Earth sciences
Earth, ocean, space
Exact sciences and technology
Genetic algorithms
Hydrology. Hydrogeology
irrigated farming
Irrigation
irrigation management
irrigation requirement
Irrigation systems
irrigation water
linear models
Linear programming
Mutation
Population number
Studies
Water requirements
Water resources
title Irrigation planning using Genetic Algorithms
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