基于多目标遗传算法的城市内涝调蓄池规模优化方法研究

A NOVEL VOLUME OPTIMIZATION METHOD FOR DETENTION TANKS FOR FLOODING IMMIGRATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHM

调蓄池是缓解城市内涝广泛应用的技术措施之一,但目前调蓄池在工程应用过程中存在设计不合理、缺乏整体效益分析等问题。为有效缓解城市内涝,提出了一种基于InfoWorks ICM模型和多目标遗传算法相耦合的调蓄池规模优化方法,并以某城市片区为例对该方法进行应用。采用InfoWorks ICM模型分析了积水内涝风险,得出5,10,20年一遇降雨重现期下片区积水点溢流总量分别为14355,17102,19838 m^(3),将上述结果与多目标遗传算法进行耦合,以降低工程造价和内涝风险为目标函数,以调蓄池占地面积和效率指数为约束条件,分别在不同降雨重现期下提出了5种优化方案,通过比较5,10,20年一遇降雨重现期下最优解的分布特征,确定方案2为最优方案,所对应的调蓄池造价为2713万,4612万,6240万元。因此,InfoWorks ICM模型与遗传算法相耦合的方法,可用于城市内涝调蓄池的规模优化设计。

With the rapid development of urbanization,the impervious area increased markedly.The detention tank is one of the important measures to alleviate urban flooding.However,the application of detention tanks faces many problems,such as the unreasonable design method,and a lack of lost-benefit analysis.A novel optimization method of the detention tank based on the coupling of InfoWorks ICM and the multi-objective genetic algorithm was proposed.Taking an urban area as an example,the waterlogging area and detention volume were analyzed by InfoWorks ICM.The total overflow volume of ponding points in the area was 14355 m^(3),17102 m^(3) and 19838 m^(3) under the 5-year,10-year and 20-year return periods of rainfall.Coupled the above results with the multi-objective genetic algorithm,with the reduction of project cost and waterlogging risk as the objective function,and with the floor area and efficiency index of the reservoir as the constraint condition,five optimization schemes were proposed.By comparing the distribution characteristics of the optimal solution under 5-year,10-year,20-year rainfall return periods,scheme 2 was determined as the optimal scheme,and the corresponding construction cost of the storage tanks was 2713,4612,62.4 million yuan.Therefore,the method of coupling the InfoWorks ICM model with genetic algorithm can be used to optimize the scale of urban waterlogging storage ponds.