Water Allocation Model Based on Coevolutionary Particle Swarm Optimization Algorithm and Its Application
This paper addressed the characteristics of multi-objective,multi-variable,complex constraints,non-linear solution results and difficult solution process of urban water resources allocation issues in the new development stage.In response to the issues of unreasonable so-lution results,low computational efficiency and slow convergence of traditional optimization algorithms such as linear programming,dynamic programming and non-linear programming in solving water resources allocation issues,a multi-objective water resources allocation model based on coevolutionary particle swarm optimization(CPSO)was proposed.The water resources allocation model was built with the objective of maximising social,economic and ecological benefits,and water supply,water demand,water supply capacity and reservoir capacity by taking Zhengzhou as an example.Through inputting the water demand and water availability of each calculation unit and sector in Zhengzhou,the model calculated and output the proportion of water shortage in the nine districts of Zhengzhou in 2019 and 2035.The results show that the regional distribution of water supply in Zhengzhou City is relatively balanced,and the water shortage rate is within an acceptable range.The algorithm of this model has a fast evolutionary speed and good evolutionary stability.The advantageous results can be well preserved in the population and have strong dominance over the evolutionary direction.It can be effectively applied to solve water resources allocation is-sues and improve the computational efficiency of the model,providing technical support for water resources management departments.
coevolutionparticle swarm optimizationoptimal allocation of water resourcesZhengzhou City
万方数据
维普
