The The Kunan Highway Median Strip Micro-irrigation Systems Of Nonlinear Programming Model

Regarding the problems in the design of Micro-irrigation system in expressway separated region from Kunming to Anning. Nonlinear mathematics planning model of Micro-irrigation system is established by means of theoretical analysis combing with engineering examples in this paper. Networks pipeline optimistic design can effectively reduce the overall investment of Micro-irrigation, it is significant to further promote the multiplex development of Micro-irrigation technology.On the basis of summarizing the domestic and foreign development dynamic and the current situation of analyzing the Micro-irrigation Network pipeline optimization, three aspects of content is studied mainly in this paper.(1) Divide Micro-irrigation group and determine the diameter and length of network pipeline of all levels by using conventional designed methods, and calculate the Hydraulic loss along trip to determine the type of water pumps.(2) We analyze the designing method of conventional Micro-irrigation system, and on this basis, we establish nonlinear mathematics planning models by means of discrete pipe diameter and by setting the pipe diameter and water pumps lift decision variable for purpose of the minimum of annual cost or investment, it will provide the technical foundations for network pipeline optimistic design and choosing reasonable irrigation system in evaluation of investment.(3) We study the genetic algorithms in nonlinear optimistic design. In recent years, genetic algorithms are widely used in the design of urban water distribution networks, but it is seldom used in Micro-irrigation networks. This paper applies genetic algorithms to solve the multivariate and nonlinear optimistic model of micro-irrigation system with characteristic of discrete, the corresponding C+ + programming is given, combing with the example of micro-irrigation in expressway separated region from Kunming to Anning, the result is satisfied. A better result is obtained through the example by the Genetic Algorithm in solving such problems.