扬州大学学报(自然科学版)2024,Vol.27Issue(3) :1-9.DOI:10.19411/j.1007-824x.2024.03.001

基于NSGA-Ⅲ算法的低影响开发措施规划设计

Planning and design of low impact development measures based on NSGA-Ⅲ algorithm

张慧颖 任亚铮 胡朝仲 毛谨 张淼 马自飞 程阳 李雪龙 范俊楠
扬州大学学报(自然科学版)2024,Vol.27Issue(3) :1-9.DOI:10.19411/j.1007-824x.2024.03.001

基于NSGA-Ⅲ算法的低影响开发措施规划设计

Planning and design of low impact development measures based on NSGA-Ⅲ algorithm

张慧颖 1任亚铮 1胡朝仲 2毛谨 1张淼 3马自飞 1程阳 1李雪龙 1范俊楠1
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作者信息

  • 1. 云南农业大学水利学院,昆明 650500
  • 2. 云南水利水电职业学院水利工程学院,昆明 650201
  • 3. 昆明理工大学建筑工程学院,昆明 650031
  • 折叠

摘要

为完善海绵城市建设的整体规划设计,基于东南亚某经济开发区,结合雨洪管理模型(storm water management model,SWMM)和第三代非支配排序遗传算法(non-dominated sorting genetic algorithm-Ⅲ,NSGA-Ⅲ)建立了一个四目标优化模型,以地表径流系数、管道过载时间、节点溢流量等3个城市内涝指标和总投资成本作为优化目标进行求解.结果表明:该优化模型可实现多目标同步优化,获得效益较高的低影响开发(low impact development,LID)措施的设计方案,优化后地表径流系数为0.309~0.355,管道过载时间为23.834~27.967 h,节点溢流量为10 477~21 802 m3,工程总投资成本为7.479亿~9.593亿元.研究结果可为未来海绵城市内涝控制设计提供技术参考.

Abstract

In order to improve the overall planning and design of sponge city construction,a four-objective optimization model is developed based on an economic development zone in Southeast Asia,combining the storm water management model(SWMM)and the non-dominated sorting ge-netic algorithm-Ⅲ(NSGA-Ⅲ).It takes three urban waterlogging indicators such as surface runoff coefficient,pipeline overload time,node overflow flow and the total investment cost as the optimi-zation objective to solve the problem.The results show that the optimization model can achieve multi-objective synchronous optimization,and obtain the design scheme of low impact development(LID)measures with high benefits.After optimization,the optimized surface runoff coefficient ran-ges from 0.309 to 0.355,the pipe overload time ranges from 23.834 to 27.967 h,the node overflow flow rate ranges from 10 477 to 21 802 m3,and the total investment cost of the project is 747.9 mil-lion to 959.3 million yuan.The research results can provide technical reference for the design of flood control in sponge cities in the future.

关键词

城市内涝/低影响开发/第三代非支配排序遗传算法/雨洪管理模型/优化设计

Key words

urban flooding/low impact development(LID)/non-dominated sorting genetic algorithm-Ⅲ(NSGA-Ⅲ)/storm water management model(SWMM)/optimization design

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基金项目

云南省科技厅科技计划资助项目(202301AT070490)

云南省教育规划单位资助项目(BE22037)

云南水利水电职业学院重点实验室开放课题研究基金资助项目(2023SZYKL003)

出版年

2024
扬州大学学报(自然科学版)
扬州大学

扬州大学学报(自然科学版)

影响因子:0.473
ISSN:1007-824X
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