GA In Optimizing The Auxiliary Sewerage Pipe Network Projects Of Shabei Sewage Treatment Plant Of Zhoukou City

In order to seek the methods of optimization of sewerage pipe network, both home and overseas experts have been working hardly. And with the development of systematic analysis methods, calculation techniques and computer, Genetic Algorithms(GA), which is becoming a new search algorithm for global optimization, has its own unique superiority in engineering optimization field because it is simple and easy use, can get satisfied results for many optimization problems, suits for parallel disposal and has no special requirements for the objective function and the bounds for it.Based on systematic studying the simple GA and the calculation methods of the sewerage pipe netAvork, the article does the following works for optimizing the parameter providing the layout of the sewerage pipe network:1. Being satisfied to the normal constraint conditions, the article settles sewerage pipe network optimization by choosing little design velocity and larger design sufficient fullness. And the article gives different maximum design velocity limit for different pipe diameter: DN300～1000mm, v_max≤1.0m/s; DN100～1200mm, v_max≤1.1m/s; DN1300～1600 mm, v_max≤1.2m/s.2. The article gets available pipe diameter population by natural number coding, which directly expresses the correspondence relationship between genetic code and standard pipe diameters in the market. And it also improves optimum efficiency of simple GA by using competition measure among generations and population singlet strategy. After lots of experiments on computer, it finally gets the genetic operators for sewerage pipe network optimization: maximum generation is 200, crossover probability P_c=0.8 and mutation probability P_m=0.4.3. The article uses the improved GA to optimize the auxiliary sewerage pipe network projects of Shabei sewage treatment plant of Zhoukou city. By comparing with the outcomes of traditional algorithm, it gets the following results:①GA can get more appropriate association of pipe diameter, sufficient fullness and inbuilt with satisfaction to all constraint conditions and save project investment about 14%.②Using GA in optimization, it just needs to input the value of flow and ground elevation at first, and can get optimization results more fast and conveniently in 13 minutes. (3) It can get lots of feasible programs and provide more choosing chances for scheme comparison and decision.The results indicate it can get more appropriately available pipe diameter assemble by choosing little design velocity and larger design sufficient fullness and different velocity limits for different pipe diameter, and can get optimization results of sewerage pipe network with high efficiency by using improved GA which uses natural number coding and competition measure among generations and population singlet strategy. The high efficient GA provides a good base for sewerage pipe network layout optimization and establishes a path for using GA in the sewerage pipe network field.