عنوان مقاله [English]
نویسنده [English]چکیده [English]
The high cost problem of urban water supply systems, along with the complexity of the design and unsuitable operation problems cause that optimization of the system before applying any changes, has become the basic needs of managers in this area. Due to the complexity of nonlinear and unique design of these networks, in recent years engineers using artificial intelligence and search algorithms to solve this problem. In the present study find solutions for the network in a town of Kerman with help of fast messy Genetic and firefly Algorithms and network simulation software intended WaterGEMS. First the water supply network in the study area simulated in WaterGEMS model and the properties required for optimization algorithms have been extract, then using the standard pressure and speed constraints, these algorithms create optimal choices. By entering these results in WaterGEMS model and re-running for limits check, the cost estimates are discussed and compared. The results show that the optimization of, fast messy Genetic algorithm with 37.7% is able to reduce the cost function of network compare to pre-optimized network. Also Firefly algorithm in the amount of 34.4%, is able to reduce costs. Finally, we can say that both optimization algorithms used in this study have been able to achieve a dramatic reduction in project costs.