Genetic Algorithms in Irrigation Planning: A Case Study of Sri Ram Sagar Project, India
作者： K. Srinivasa Raju , D. Nagesh Kumar
DOI: 10.1007/978-3-540-39930-8_16
关键词: Penalty method 、 Linear programming 、 Fitness function 、 Population size 、 Geography 、 Mutation (genetic algorithm) 、 Water resource management 、 Statistics 、 Agricultural diversification 、 Irrigation 、 Crossover
摘要: The present study deals with application of Genetic Algorithms (GA) in the field irrigation planning. GA technique is used to achieve efficient operating policy objective maximum net benefits for case Sri Ram Sagar Project, Andhra Pradesh, India. Constraints include continuity equation, land and water requirements, crop diversification considerations, restrictions on storage capacities. Penalty function approach convert constrained problem into unconstrained one. For fixing parameters, namely, crossover mutation probabilities, model run 7 values 6 probabilities. It found that appropriate parameters such as number generations, population size, probability, probability are 200, 50, 0.6 0.01 respectively study. Maximum obtained by LP solution 2.4893 Billion Rupees where these 2.3903 (with a fitness value 2.3678 Rupees). Results compared Linear Programming be reasonably close.
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