Research On The Optimal Design Of Water Supply Network By IGAPSO Algorithm

Water supply network as an important part of urban water supply system is composed of a variety of water supply facilities of urban water supply distribution system and is the important basic livelihood facilities of urban construction and economic development. Generally, water supply network’s investment accounts for the50-80percent of total investment. The rationality of water supply network design not only can affect the annual operating cost but also can affect the reliability and safety of the whole city water supply. Therefore, in the design phase of the water supply network, it has great significance to the optimal design of water supply network and has also become one of the research directions of the current municipal researchers.On the basis of theoretical analysis of the water supply network optimization model, genetic algorithm and particle swarm optimization, this article uses IGAPSO (Improved Genetic Algorithm-Particle Swarm Optimization) algorithm which is an improved algorithm combined by particle swarm optimization and genetic algorithm to study on the optimal design of water supply network. This article uses an instance of the application to test IGAPSO algorithm and achieves good results.This article first introduces the background and meaning of the optimal design of water supply network and the present situation of the optimization algorithm. Then, based on the analysis of the mathematical model of water supply network and the related hydraulic calculation theory, this article considers that it will be more suitable to the needs of the engineering that uses the dynamical objective function of water supply network.Then, this article respectively expounds genetic algorithm and particle swarm optimization and introduces the principle, calculation process and characteristics of two algorithms. On this basis, this article puts forward IGAPSO algorithm which is an improved algorithm combined by genetic algorithm and particle swarm optimization to the water supply network optimization.Because the inertia weight, the cognitive coefficient and the social coefficient have great influences on particle swarm optimization in IGAPSO algorithm, this article uses the stepwise linear decrease or increase strategy in order that IGAPSO algorithm can give full play to the global best particle and the local particle effect in the process of evolution, and maintain stability of group evolution. Because particle swarm optimization based on group search can’t know in advance the search issues and judge group premature convergence problem, IGAPSO algorithm gives up to use the crossover operation used in the general GAPSO algorithm, and uses the mutation operation coming form genetic algorithm, In order to improve the group diversity, it uses the random variation of neighborhood controlled in the feasible diameter range. Through the use of these improvement measures, IGAPSO algorithm are effective in increasing population diversity, improving the global search capabilities of the algorithm, can help the algorithm overcome the group premature convergence problems.Finally, this article through a engineering examples analysis shows that the optimal design results of water supply network in economy used by IGAPSO algorithm is more better than the results used by particle swarm optimization in the case of reliability to satisfy. Therefore, IGAPSO algorithm has an important practical value in the optimal design of water supply network.