基于改进粒子群算法的城市给水管网优化设计

发布时间：2018-01-28 05:13

本文关键词： 粒子群混合优化算法给水管网动态调整自适应惩罚函数决策系统　出处：《北京工业大学》2014年硕士论文　论文类型：学位论文

【摘要】：城市给水管网系统是城市建设和工业生产的重要基础设施，，随着城市规模的扩大，管网系统的规模也逐渐呈现出复杂化、大型化的发展趋势，管网系统的建设资金投入也随之增加。一般给水管网的投资占到工程总投资的四分之三，通过优化计算，可以节省工程投资的5%—10%，具有巨大的经济效益和现实意义。如何对给水管网进行科学的优化设计已经成为国内外专家关注的问题。粒子群优化算法机制简单、可调参数少、易于实现，具有较强的全局收敛能力，不需要借助问题的特征信息等特点，因此文中采用粒子群优化算法对城市给水管网进行优化设计。论文的主要研究工作如下： 1.针对标准粒子群优化算法在优化给水管网问题中存在易陷入局部最小难以寻求最优解的问题，文中在分析粒子群优化算法的惯性权重对算法性能影响的基础上，提出了一种基于粒子聚集程度动态调整惯性权重的策略，该调整策略利用种群在进化过程中粒子分布信息动态改变惯性权值，充分平衡了算法在优化过程中全局探索能力和局部开发能力，提高了算法的寻优精度。利用4个典型的基准测试函数对改进的算法进行测试。测试结果表明，改进的算法与传统的ω调整策略相比更能够适应粒子动态搜索的性能。 2.为了解决给水管网优化设计这样一类带有约束条件的、高度非线性的离散组合优化问题，提出一种改进型粒子群混合优化算法。该算法在动态调整惯性权重的改进基础之上，将极值优化算法引入到改进粒子群算法中，利用极值优化算法精细的局部搜索能力，增加种群多样性并使算法有效地跳出局优。根据给水管网优化设计问题的最优解分布的特点，采用自适应惩罚函数法处理管网优化的约束条件，提高算法的搜索效率。将改进型粒子群混合优化算法应用到给水管网优化设计中，仿真结果表明，算法有较好收敛速度的同时还有效地避免了陷入局部最优，并得到了更优的工程造价。 3.开发了单机版给水管网智能计算决策系统软件。该系统软件使用VS2010和MATLAB作为开发工具，嵌入多种智能优化算法及新提出的改进算法，对给水管网进行优化计算，迅速、准确地得到管网总造价和最优管径的结果，实现在管线的铺设阶段根据实际情况提供优化决策的功能，通过设置管网运行、造价的不同参数，分析对比数据结果为决策者提供更优的选择。通过C#设计界面，使系统软件的操作具有直观性和可视性。论文针对粒子群优化算法在解决给水管网优化问题所存在的问题，对算法进行了改进研究，提出一种改进型粒子群混合优化算法并将其应用在城市给水管网优化设计中。在满足供水要求的前提下，取得了较优的结果。并利用Visual Studio2010和MATLAB等工具开发了给水管网智能计算决策系统，为城市规划设计、建设等提供基础数据支撑。
[Abstract]:Urban water supply network system is an important infrastructure for urban construction and industrial production. With the expansion of the scale of the city, the scale of the pipe network system also gradually presents a complex, large-scale development trend. The investment of water supply network accounts for 3/4 of the total investment of the project. Through the optimization calculation, it can save 5- 10% of the project investment. It is of great economic benefit and practical significance. How to optimize the water distribution network scientifically has become a problem that experts at home and abroad pay close attention to. Particle swarm optimization (PSO) has the advantages of simple mechanism, few adjustable parameters, easy implementation, strong global convergence ability and no need for the characteristic information of the problem. Therefore, particle swarm optimization algorithm is used to optimize the design of urban water distribution network. The main research work of this paper is as follows: 1. Aiming at the problem that the standard particle swarm optimization algorithm is easy to fall into the local minimum, it is difficult to find the optimal solution in the optimization of water supply network. On the basis of analyzing the influence of inertia weight of particle swarm optimization algorithm on the performance of the algorithm, a strategy of dynamically adjusting inertia weight based on particle aggregation degree is proposed in this paper. The adjustment strategy uses the information of particle distribution to change the inertia weight dynamically in the process of population evolution, and balances the global exploration ability and local development ability of the algorithm in the process of optimization. The improved algorithm is tested by using four typical benchmark functions. The test results show that the proposed algorithm can be used to improve the accuracy of the algorithm. 4 typical benchmark functions are used to test the improved algorithm. Compared with the traditional 蠅 adjustment strategy, the improved algorithm is more suitable for particle dynamic search. 2. In order to solve this kind of highly nonlinear discrete combinatorial optimization problem with constraints, the optimal design of water supply network is solved. An improved particle swarm optimization (PSO) hybrid optimization algorithm is proposed, which is based on the dynamic adjustment of inertia weight, and the extremum optimization algorithm is introduced into the improved PSO algorithm. By using the fine local search ability of the extremum optimization algorithm, the population diversity is increased and the algorithm effectively jumps out. According to the characteristics of the optimal solution distribution of the water supply network optimization design problem. Adaptive penalty function method is used to deal with the constraint conditions of pipe network optimization, and the search efficiency of the algorithm is improved. The improved particle swarm optimization algorithm is applied to the optimization design of water supply network. The algorithm has better convergence speed and effectively avoids falling into local optimum and gets better project cost. 3. The software of intelligent calculation and decision system for water supply network is developed, which uses VS2010 and MATLAB as developing tools. A variety of intelligent optimization algorithms and new improved algorithms are embedded to optimize the water supply network. The results of the total cost and the optimal diameter of the pipe network are obtained quickly and accurately. In the pipeline laying stage according to the actual situation to provide the function of optimal decision-making, through setting up the pipeline network operation, the cost of different parameters. Through the C # design interface, the operation of the system software is intuitive and visible. Aiming at the problem of particle swarm optimization algorithm in solving the problem of water supply network optimization, the improvement of the algorithm is studied in this paper. An improved particle swarm optimization algorithm is proposed and applied to the optimal design of urban water supply network. The intelligent calculation decision system of water supply network is developed by using Visual Studio2010 and MATLAB tools, which can be used for urban planning and design. Construction to provide basic data support.
【学位授予单位】：北京工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TU991.33;TP18

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