基于多决策变量协同设计的供水管网多目标优化模型研究
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摘要
在城镇供水管网设计中,管线布置和管径搭配是影响工程经济性和可靠性的重要因素。为提升管网设计的整体优化水平,以管线布置和管径搭配共同作为决策变量,选用"管网建造费用"作为经济性目标函数,选用"管网管段压力均值"、"管网恢复力"和"枝状管流量和"作为管网可靠性目标函数,建立供水管网多目标优化设计模型。使用MATLAB平台搭载EPANET2动态链接库,采用改进的非支配排序多目标遗传算法(NSGA-Ⅱ)求解模型得到帕累托(Pareto)前沿解集,并使用多标准优化和妥协解决方案(VIKOR)法选出最优折衷设计方案。最后以广东省某城镇供水管网设计为例进行验证,得到的前沿解集在多维目标空间中分布均匀,且选出的最优折衷方案综合效益良好,证明了供水管网管线布置和管道尺寸协同设计的科学性和有效性。
In the design of urban water supply network, pipeline layout and pipe diameter are important factors affecting the economic and reliability of the project. In order to improve the overall optimization level of the pipe network design, pipeline layout and the pipe diameter are combined as the decision variables, "pipe network construction cost" as the economic objective function, and select "pipe network pipe pressure mean", "pipe network resilience" and "sum flow of branch pipe" as the pipe network reliability objective function, to establish a multi-objective optimization design model of the water supply network. On the MATLAB platform with the EPANET2 dynamic link library, use the improved non-dominated sorting multi-objective genetic algorithm(NSGA-Ⅱ) to solve the model and obtain the Pareto frontier solution set, then use Vlsekriterijumska Optimizacija I Kompromisno Resenje(VIKOR) method to choose the optimal compromise design. Finally, the design of a water supply network in a certain town in Guangdong Province is taken as an example to verify that the obtained front-end solution set is evenly distributed in the multi-dimensional target space, and the selected optimal compromise scheme has good comprehensive benefits, which proves the scientific and effective design of water supply pipe network pipeline layout and pipeline diameter collaborative design.
In the design of urban water supply network, pipeline layout and pipe diameter are important factors affecting the economic and reliability of the project. In order to improve the overall optimization level of the pipe network design, pipeline layout and the pipe diameter are combined as the decision variables, "pipe network construction cost" as the economic objective function, and select "pipe network pipe pressure mean", "pipe network resilience" and "sum flow of branch pipe" as the pipe network reliability objective function, to establish a multi-objective optimization design model of the water supply network. On the MATLAB platform with the EPANET2 dynamic link library, use the improved non-dominated sorting multi-objective genetic algorithm(NSGA-Ⅱ) to solve the model and obtain the Pareto frontier solution set, then use Vlsekriterijumska Optimizacija I Kompromisno Resenje(VIKOR) method to choose the optimal compromise design. Finally, the design of a water supply network in a certain town in Guangdong Province is taken as an example to verify that the obtained front-end solution set is evenly distributed in the multi-dimensional target space, and the selected optimal compromise scheme has good comprehensive benefits, which proves the scientific and effective design of water supply pipe network pipeline layout and pipeline diameter collaborative design.
引文
[1] 赵洪宾.给水管网系统理论与分析[M].北京: 中国建筑出版社, 2003.
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[10] 余嵘,严程,逯佩宁.自适应罚函数遗传算法对给水管网优化的研究[J].给水排水,2016,52(4):136-140.
[11] Kayvanfar V, Husseini S M M, Karimi B, et al. Bi-objective intelligent water drops algorithm to a practical multi-echelon supply chain optimization problem [J]. Journal of Manufacturing Systems, 2017,44(1): 93-114.
[12] 乔俊飞,魏静,韩红桂.基于改进NSGA2算法的给水管网多目标优化设计[J].控制工程,2016,23(12):1861-1866.
[13] 周荣敏,林性粹.应用单亲遗传算法进行树状管网优化布置[J].水利学报,2001(06):14-18.
[14] Tanabe R, Ishibuchi H. An analysis of control parameters of MOEA/D under two different optimization scenarios [J]. Applied Soft Computing, 2018, 70: 22-40.
[15] Opricovic S, Tzeng G H. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS [J]. European Journal of Operational Research, 2004,156(2): 445-455.
[16] Laumanns M, Thiele L, Deb K, et al. Combining convergence and diversity in evolutionary multiobjective optimization [J]. Evolutionary Computation, 2002, 10(3): 263-282.
[2] 刘书明,王欢欢,徐锦华,等.基于智能优化算法的供水管网漏水点定位[J].同济大学学报(自然科学版),2014,42(05):740-744.
[3] 李海滨,马孝义,赵文举,等.树状管网布置与管径同步优化方法研究[J].系统仿真学报,2009,21(11):3180-3183.
[4] 姚慰炜,马孝义,王向伟,等.自适应遗传算法在环状管网水力计算中的优化设计[J].灌溉排水学报,2010,29(4):85-88.
[5] Moosavian N, Lence B J. Nondominated sorting differential evolution algorithms for multiobjective optimization of water distribution systems [J]. Journal of Water Resources Planning and Management, 2016,143(4):040160824.
[6] Krapivka A, Ostfeld A. Coupled genetic algorithm-linear programming scheme for least-cost pipe sizing of water-distribution systems [J]. Journal of Water Resources Planning and Management, 2009, 135(4): 298-302.
[7] Wang X, Zhao Y, Wang D, et al. Improved multi-objective ant colony optimization algorithm and its application in complex reasoning [J]. Chinese Journal of Mechanical Engineering, 2013,26(5): 1031-1040.
[8] Hotlos H. Quantitative assessment of the influence of water pressure on the reliability of water-pipe networks in service [J]. Environment Protection Engineering, 2010,36(3): 103-112.
[9] 柳晓明. 基于自适应粒子群算法的城市给水管网优化设计[D].重庆:重庆大学,2012.
[10] 余嵘,严程,逯佩宁.自适应罚函数遗传算法对给水管网优化的研究[J].给水排水,2016,52(4):136-140.
[11] Kayvanfar V, Husseini S M M, Karimi B, et al. Bi-objective intelligent water drops algorithm to a practical multi-echelon supply chain optimization problem [J]. Journal of Manufacturing Systems, 2017,44(1): 93-114.
[12] 乔俊飞,魏静,韩红桂.基于改进NSGA2算法的给水管网多目标优化设计[J].控制工程,2016,23(12):1861-1866.
[13] 周荣敏,林性粹.应用单亲遗传算法进行树状管网优化布置[J].水利学报,2001(06):14-18.
[14] Tanabe R, Ishibuchi H. An analysis of control parameters of MOEA/D under two different optimization scenarios [J]. Applied Soft Computing, 2018, 70: 22-40.
[15] Opricovic S, Tzeng G H. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS [J]. European Journal of Operational Research, 2004,156(2): 445-455.
[16] Laumanns M, Thiele L, Deb K, et al. Combining convergence and diversity in evolutionary multiobjective optimization [J]. Evolutionary Computation, 2002, 10(3): 263-282.