Irrigation Planning using Genetic Algorithms

Authors: Srinivasa Raju K.¹; Nagesh Kumar D.²

Source: Water Resources Management, Volume 18, Number 2, April 2004 , pp. 163-176(14)

Publisher: Springer

Buy & download fulltext article:

Price: $47.00 plus tax (Refund Policy)

Abstract:

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.

Keywords: cropping pattern; genetic algorithms; irrigation planning; linear programming

Document Type: Research article

DOI: http://dx.doi.org/10.1023/B:WARM.0000024738.72486.b2

Affiliations: 1: Civil Engineering Department, Birla Institute of Technology and Science, Pilani, India 2: Civil Engineering Department, Indian Institute of Science, Bangalore, India (author for correspondence, nagesh@civil.iisc.ernet.in), Email: nagesh@civil.iisc.ernet.in

Publication date: 2004-04-01