Fusegates selection and operation: simulation-optimization approach

被引:4
|
作者
Afshar, Abbas [3 ]
Takbiri, Zeinab [1 ,2 ]
机构
[1] Univ Minnesota, Dept Civil Engn, St Anthony Falls Lab, Minneapolis, MN 55414 USA
[2] Univ Minnesota, Natl Ctr Earth Surface Dynam, Minneapolis, MN USA
[3] Iran Univ Sci & Technol, Dept Civil Engn, Tehran 16844, Iran
关键词
flood routing; fusegates; hydraulic simulation; optimization; spillway;
D O I
10.2166/hydro.2011.154
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Fusegates present a reliable and cost-effective alternative, which increase flood protection and water supply benefits. This article develops a comprehensive simulation-optimization framework for practical selection, installation, and operation of fusegates. The computational model simulates the complicated hydraulic behavior of fusegates systems with varying design characteristics and consequential anomalous routing process in case of flood events. An efficient mixed genetic algorithm (GA) is subsequently developed and coupled with the highly nonlinear hydraulic simulation model to minimize the overall expected annual cost under structural, hydraulic, and operational constraints. Types, heights, and tipping heads of gates are explicitly treated as optimization decision variables. Furthermore, the frequent practice of installing all gates in the same level is practically improved to favorably help minimize water loss in case of moderate discharge floods. The proposed model is demonstrated and discussed for a case study of the Taleghan Dam fusegates installation project in Iran. A series of sensitivity analyses are also conducted to assess routing effect and uncertainty in water unit price and replacement costs and provide more insight and understanding of the design problem.
引用
收藏
页码:464 / 477
页数:14
相关论文
共 50 条
  • [1] A simulation-optimization approach using genetic search for supplier selection
    Ding, HW
    Benyoucef, L
    Xie, XL
    [J]. PROCEEDINGS OF THE 2003 WINTER SIMULATION CONFERENCE, VOLS 1 AND 2, 2003, : 1260 - 1267
  • [2] Simulation-optimization model for reservoir flood control operation
    Wang, YM
    Huang, Q
    Zhang, SH
    [J]. JOURNAL OF EXPERIMENTAL BOTANY, 2003, 54 : 52 - 52
  • [3] A Simulation-Optimization Approach to Estimate Workforce Requirements
    Zais, Mark
    Laguna, Manuel
    [J]. MILITARY OPERATIONS RESEARCH, 2017, 22 (01) : 19 - 37
  • [4] Hybrid MCDM and simulation-optimization for strategic supplier selection
    Saputro, Thomy Eko
    Figueira, Goncalo
    Almada-Lobo, Bernardo
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2023, 219
  • [5] Preventive maintenance scheduling: a simulation-optimization approach
    Darmawan, Agus
    Sheu, D. Daniel
    [J]. PRODUCTION AND MANUFACTURING RESEARCH-AN OPEN ACCESS JOURNAL, 2021, 9 (01): : 281 - 298
  • [6] SIMULATION-OPTIMIZATION USING A REINFORCEMENT LEARNING APPROACH
    Paternina-Arboleda, Carlos D.
    Montoya-Torres, Jairo R.
    Fabregas-Ariza, Aldo
    [J]. 2008 WINTER SIMULATION CONFERENCE, VOLS 1-5, 2008, : 1376 - +
  • [7] A simulation-optimization approach for solving the forestry logistics problem
    Sibdari, Soheil Y.
    Sepasi, Amir H.
    [J]. IFAC PAPERSONLINE, 2022, 55 (10): : 3178 - 3183
  • [8] A COMBINED SIMULATION-OPTIMIZATION APPROACH FOR PREDICTING CROP YIELDS
    SWANEY, DP
    JONES, JW
    MISHOE, JW
    BAKER, F
    [J]. AGRICULTURAL SYSTEMS, 1986, 20 (02) : 133 - 157
  • [9] A simulation-optimization approach for integrated sourcing and inventory decisions
    Keskin, Burcu B.
    Melouk, Sharif H.
    Meyer, Ivan L.
    [J]. COMPUTERS & OPERATIONS RESEARCH, 2010, 37 (09) : 1648 - 1661
  • [10] An Efficient Simulation-Optimization Approach for Controlling Seawater Intrusion
    Yang, Yun
    Wu, Jianfeng
    Lin, Jin
    Wang, Jinguo
    Zhou, Zhifang
    Wu, Jichun
    [J]. JOURNAL OF COASTAL RESEARCH, 2018, : 10 - 18