给水管网混沌粒子群优化算法及模型实验研究

Optimal design and model experiment of water supply network based on improved multi-objective particle swarm optimization

针对传统管网优化模型存在的优化目标局限、优化效率低等问题,提出了基于混沌粒子群算法的改进管网多目标优化模型,选取给水管网经济性、可靠性进行数学表征,以此为目标函数,将水力约束和节点压力限制作为约束条件。改进传统PSO,使其适用于对管网系统的多目标约束问题求解,并引入混动权重,对管网进行深度遍历,提高了管网优化效率。最后引入实例,通过MATLAB模拟实验,实验表明该模型具有较好的稳定性,提高了优化效率。

Aiming at the problems of optimization target limitation and low optimization efficiency in the traditional pipe network optimization model,this paper proposes a multi-objective optimization model based on chaotic particle swarm optimization algorithm to improve the economics and reliability of water supply network.With this as the objective function,hydraulic constraints and node pressure limits are used as constraints.The traditional PSO is improved to make it suitable for solving the multi-objective constraint problem of the pipe network system,and the hybrid weight is introduced to carry out the deep traversal of the pipe network,which improves the optimization efficiency of the pipe network.Finally,an example is introduced.Through the MATLAB simulation experiment,the experiment shows that the model has good stability and improves the optimization efficiency.