Study of Corn Optimization Irrigation Model by Genetic Algorithms

Abstract

Many factors affecting irrigation model, including irrigation water volume, crop water requirement, production function of irrigation water, rainfall, soil water balance, water sensitive index in different stages of crop growth, the grain market price, irrigation water price, minimum yield, irrigation cost etc are considered. Then a multi-constraints and non-linear optimization irrigation model based on the maximal profit of irrigation water volume is set up, which is adaptive to our national conditions, and the real number encoding space of the model is searched by the powerful searching ability of genetic algorithm. The results show that this model can solve the optimization irrigation problem of summer corn, and genetic algorithm has very perfect searching function, and the optimal solution of the model can be found in very short time.