Optimization of Division Dam Section Based on Genetic Algorithm

Diversion dams in order to raise the water level of river and conveys of water into the main canal irrigation network is designed. If the dimensions of different parts of the diversion dam be considered large, stability will be supplying, but due to the increase volume of materials, construction costs will be more. Design engineer must choose sections of dam that had least amount of materials and meantime be sustainable. Optimize section of diversion dams can be calculated with classic and genetic algorithm methods. The purpose of this study evaluation the efficiency of genetic algorithm to find optimized section of diversion dam in addition to regard laws and regulations designed the least volumes of materials. Decision variables that used in this study include wall height upstream and downstream of dam, slope in the upper body, thickness of stilling basin, thickness of concrete blanket upstream and length of concrete blanket. The objective function is to minimize amount of materials is used. Design constraints used include abide the stability of dam safety factors against Piping, Sliding, overturning and failure. In this research, section of Nazelian Dam by using genetic algorithm optimized and the effect of GA operators in objective function were investigated. Results show, if the genetic algorithm was used in design for overturning with a minimum safety factor of 2.1, the body weight of the dams and volume of materials decreased by 15.4%. Suitable values for the number of generation, population size, probability crossover and mutation to optimize Diversion Dam were 50, 30, 0.55 and 0.05, respectively.