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Optimization of Sprinkler Irrigation Machine Based on Genetic Algorithms

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2012 Dallas, Texas, July 29 - August 1, 2012  121341121.(doi:10.13031/2013.42061)
Authors:   Qin Tu, Xinkun Wang, Hong Li
Keywords:   Key words: Sprinkler Irrigation, Genetic Algorithms (GAs), Annual Cost, Optimization

Rational configuration and optimal design of sprinkler irrigation machine will contribute to both the performance improvement of the system and reduction in the operation cost. In this work, a mathematic optimization model of the sprinkler irrigation machine was established and the solution based on a genetic algorithm (GA) was developed. The minimal annual cost, which consisted of the specific depreciation expense and specific energy consumption fee, was defined as the objective function. The pump and pipeline operating conditions, minimal working pressure of sprinkler and sprinkler working pressure deviation range were chosen as the constraint conditions. Number of sprinklers, pipe diameter and sprinkler pressure head at the end of the pipeline were taken as the decision variables in the genetic algorithm. The back step method was employed in the hydraulic calculation of the pipeline. When the design parameters were input, the model could optimize the number of sprinklers, pipe diameter and figure out the discharge and pressure head of each sprinkler, specific cost and specific energy consumption of the machine. Therefore, both the pump and the pipeline would operate in the optimized condition. The examples showed that the procedure based on GA was robust with excellent efficiency, high accuracy, reliability, and practicability.

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