Improved Ant Colony Optimization For Upgrading And Expansion Of Water Distribution System

Urban water network is a vital part of the water supply systems, and plays an important role in securing economic construction and people's lives. With the sustained development of economy, the development of the city modernization, water demands of customers increase greatly. There are lots of problems that influence transmission of water regularly, along with deteriorating of water quality because of increasing for using time. So the developing cities are facing the problem of upgrading and expansion of water distribution system. Because of the huge investment and management cost, optimal upgrading and expansion can save much money and actualize good economic and social situation.Beginning with practical situation of the optimal upgrading and expansion of water distribution system, to forecast long-term water demand is the foundation and preparatory work. Firstly, traditional forecast model is analyzed, and improved gray model is constructed by additional data and dynamic equal dimension new data based on the shortcoming of traditional gray model. By checkout of practical data, the improved gray model has a better forecasting effect with a few data than traditional model and can be used to the practical engineering.Then the process of the optimal mathematics model is introduced, and optimization model is constructed, which includes pipe optimization, pressure pump station optimization and water resource optimization.Owing to the discrete character of the pipe diameter with the object function being a multi-model function,and optimal upgrading and expansion being complex non-linear matter, ant colony algorithm(ACA) is a new type biologic simulating algorithm and is adopted. But ACA has much deficiency, specialy it is easy to fall into the local best and its calculation is complicated. So improved ant colony optimization algorithm is put forward to improve the shortcoming of basic ant colony algorithm. These two algorithms are separately applied to a simple network optimization problem. And the results show that improved ACA is superior than basic ACA. Improved ant colony algorithm has excellent global optimization propertyes, shorter operation time and higher optimizing efficiency.In the end, an actual engineering is used to certify the rationality of the model and the optimization algorithm. The optimization algorithm and the traditional algorithm are applied to distribution system upgrading and expansion engineering in some city. And the comparison of solution illustrates the optimal plan which is designed by improved ant colony Optimization algorithm saves the cost of water networks.