Irrigation planning using genetic algorithms

被引：99

作者：

Srinivasa Raju K. ^{[1
]}

Nagesh Kumar D. ^{[2
]}

机构：

[1] Civil Engineering Department, Birla Institute of Technology/Sci., Pilani

[2] Civil Engineering Department, Indian Institute of Science, Bangalore

来源：

Water Resources Management | 2004年 / 18卷 / 02期

关键词：

Cropping pattern; Genetic algorithms; Irrigation planning; Linear programming;

D O I：

10.1023/B:WARM.0000024738.72486.b2

中图分类号：

学科分类号：

摘要：

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. © 2004 Kluwer Academic Publishers.

引用

页码：163 / 176

页数：13

共 28 条

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