Comparative study of optimization techniques for irrigation project planning
Journal
Journal of the American Water Resources Association
Journal Volume
39
Journal Issue
1
Pages
59-73
Date Issued
2003
Author(s)
Abstract
ABSTRACT: This study presents three optimization techniques for on‐farm irrigation scheduling in irrigation project planning: namely the genetic algorithm, simulated annealing and iterative improvement methods. The three techniques are applied to planning a 394.6 ha irrigation project in the town of Delta, Utah, for optimizing economic profits, simulating water demand, and estimating the crop area percentages with specific water supply and planted area constraints. The comparative optimization results for the 394.6 ha irrigated project from the genetic algorithm, simulated annealing, and iterative improvement methods are as follows: (1) the seasonal maximum net benefits are $113,826, $111,494, and $105,444 per season, respectively; and (2) the seasonal water demands are 3.03*10 3 m 3 , 3.0*10 3 m 3 , and 2.92*10 3 m 3 per season, respectively. This study also determined the most suitable four parameters of the genetic algorithm method for the Delta irrigated project to be: (1) the number of generations equals 800, (2) population size equals 50, (3) probability of crossover equals 0.6, and (4) probability of mutation equals 0.02. Meanwhile, the most suitable three parameters of simulated annealing method for the Delta irrigated project are: (1) initial temperature equals 1,000, (2) number of moves equal 90, and (3) cooling rate equals 0.95.
SDGs
Type
journal article