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WANG Jianlong, ZHANG Changhe, XI Guangpeng. A NOVEL VOLUME OPTIMIZATION METHOD FOR DETENTION TANKS FOR FLOODING IMMIGRATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHM[J]. ENVIRONMENTAL ENGINEERING , 2023, 41(6): 166-173. doi: 10.13205/j.hjgc.202306022
Citation: WANG Jianlong, ZHANG Changhe, XI Guangpeng. A NOVEL VOLUME OPTIMIZATION METHOD FOR DETENTION TANKS FOR FLOODING IMMIGRATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHM[J]. ENVIRONMENTAL ENGINEERING , 2023, 41(6): 166-173. doi: 10.13205/j.hjgc.202306022

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

doi: 10.13205/j.hjgc.202306022
  • Received Date: 2022-11-11
    Available Online: 2023-09-02
  • 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 m3, 17102 m3 and 19838 m3 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.
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