• Title/Summary/Keyword: Multi-Objective Genetic Algorithms(MOGAs)

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Optimization of Detention Facilities by Using Multi-Objective Genetic Algorithms (다목적 유전자 알고리즘을 이용한 우수유출 저류지 최적화 방안)

  • Chung, Jae-Hak;Han, Kun-Yeun;Kim, Keuk-Soo
    • Journal of Korea Water Resources Association
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    • v.41 no.12
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    • pp.1211-1218
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    • 2008
  • This study is for design of the detention system distributed in a watershed by the Multi-Objective Genetic Algorithms(MOGAs). A new model is developed to determine optimal size and location of detention. The developed model has two primary interfaced components such as a rainfall runoff model to simulate water surface elevation(or flowrate) and MOGAs to get the optimal solution. The objective functions used in this model depend on the peak flow and storage of detention. With various constraints such as structural limitations, capacities of storage and operational targets. The developed model is applied at Gwanyang basin within Anyang watershed. The simulation results show the maximum outlet reduction is occurred at detention facilities located in upper reach of watershed in the peak discharge rates. It is also reviewed the simultaneous construction of an off-line detention and an on-line detention. The methodologies obtained from this study will be used to control the flood discharges and to reduce flood damage in urbanized watershed.