【作者】 李明华；

【导师】 刘全；

【作者基本信息】 苏州大学 ， 计算机软件与理论， 2008， 硕士

【摘要】 本文以苏州市污水管道系统规划项目为背景。管道系统规划通常涉及管道布局优化和管道水力参数优化两部分。通常情况下,污水管道系统投资较大,偿还期限长,这就需要提供一种比较先进、可靠的设计方法(算法)或设计平台,对污水管道进行优化设计,寻求满足各种技术条件,且能使整个系统总费用最低的设计方案。这不仅具有重要的理论和应用价值,而且具有明显的经济和社会效益。本文提出基于改进微粒群的方法,用于解决污水管道优化问题,目标是使整个污水管道系统的费用降低。本文的主要研究成果如下:(1)将离散微粒群算法应用到污水管网布局优化中。首先建立了污水管网布局优化的数学模型,将离散微粒群算法应用到该模型中。实验结果与遗传算法相比,离散微粒群算法具有更好的性能。(2)针对微粒群算法收敛速度慢及多样性丢失等问题,在基于带有微分扰动因子的微粒群优化算法基础上,提出了一种改进多种群的微粒群算法。(3)将改进多种群的微粒群算法应用到污水管道水力参数优化设计中。以苏州市管道规划为应用背景,建立相应的简化数学模型。该算法应用于污水管道水力参数优化,实验结果表明,该算法是可行和高效的。(4)开发了污水管道优化系统。依托苏州园区联图软件公司,基于改进微粒群的算法,开发了污水管道优化系统,实现了与公司原有管道系统的无缝对接。目前该系统已经应用于污水管道优化中,使整个管道系统的费用较以前有明显降低。(5)开发了污水管线管理系统。为了实现项目方式管理成果数据,根据不同管线特点,实现点线数据的快速编辑等,采用Microstation Development Language(MDL)语言在Microstation环境下开发了污水管线管理系统。目前,该系统已应用到管道局的管线产品管理中。本课题求解方法具有理论意义和应用参考价值,为继续深入研究污水管道优化设计方法提供了参考。更多还原

【Abstract】 In the paper, the engineering background is sewage pipeline system project in Suzhou city. Pipeline system planning usually involves pipeline layout optimization and pipeline hydraulic parameter optimization. In general, there is a large investment and a long repayment period for sewage pipeline system. This will need to offer a more advanced and reliable design method (algorithm) or design platform to optimize the design of the sewers, make an optimized design according to the sewage pipe network, and seek the economic and reasonable design scheme, which will have extremely vital significance.An improved particle swarm optimization (PSO) algorithm is proposed and applied to sewage pipeline optimization so that the cost of the whole system for sewage pipeline is reduced. The main research results are as follows:(1) Discrete particle swarm algorithm will be applied to optimize the layout of the sewers. First, layout optimization mathematical model for a sewage pipe network is established, and then discrete particle swarm algorithm is applied to the model. Compared with genetic algorithm (GA), the experimental results show that discrete particle swarm algorithm has better performance.(2) Based on the differential disturbance factor particle swarm optimization, an improved multi-swarm particle swarm optimization algorithm (MSPSO) is presented to solve the problem of the slow convergence and diversity issues for loss.(3) A particle swarm optimization algorithm based on improved multi-swarm is applied to hydraulic parameters optimized design of the sewers. Under the background of sewage system for the pipeline project in Suzhou city, corresponding simplified mathematical model is established. The algorithm is applied to the sewers hydraulic parameters optimization, and the experimental results show that the algorithm is feasible and efficient.(4) The sewage pipeline optimal system is developed. Based on an improved multi-swarm PSO (MSPSO) method, the sewage optimal system is developed relying on Shzhou Unimap Software co. Ltd., which is seamless with the company’s existing pipeline system. The system has been applied to optimization of the sewers so that the whole pipeline system cost is significantly lower than in the past.(5) Sewage pipeline measured system is developed. In order to achieve result data management in the way of project, according to the characteristics of different pipelines, achieve rapid data editing for point and line etc, sewage pipeline measured system is developed using Microstation Development Language (MDL) in the Microstation environment. The system has been applied to pipeline product of Pipeline Bureau at present.This research and proposed method not only benefit the development of techniques in related fields theoretically, but also it can be applied to practical application. Moreover, it makes reference for further research in the Sewage pipeline Optimization field.更多还原