University of Tabriz Water and Soil Science 2008-5133 26 2-2 2017 10 30 Multi-Objective Optimization of Detention Rockfill Dam Characteristics Considering Hydraulic Conditions and Application of Borda Count Social Choice and Nash- Harsanyi Bargaining Models Multi-Objective Optimization of Detention Rockfill Dam Characteristics Considering Hydraulic Conditions and Application of Borda Count Social Choice and Nash- Harsanyi Bargaining Models 13 25 5345 FA MR Nikoo N Khorram Journal Article 2017 10 30 Floods inflict a large amount of loss on communities and installations in Iran due to the<br />geological characteristics and environmental destructions. Detention rockfill dams are important<br />structural methods to mitigate flood damages. So, it is necessary to assess the optimum<br />characteristics of detention rockfill dams considering their hydraulic performance. In this paper, a<br />novel methodology based on data-driven simulation model, NSGA-II multi-objective optimization<br />model and game theory is suggested in order to find the optimum features of detention rockfill<br />dams. The proposed model is on the basis of the multi-objective genetic algorithm model (NSGA-<br />ΙΙ) and the multilayer perceptron neural network meta-model (MLP). The MLP meta-model<br />simulates the relationship between desig Floods inflict a large amount of loss on communities and installations in Iran due to the<br />geological characteristics and environmental destructions. Detention rockfill dams are important<br />structural methods to mitigate flood damages. So, it is necessary to assess the optimum<br />characteristics of detention rockfill dams considering their hydraulic performance. In this paper, a<br />novel methodology based on data-driven simulation model, NSGA-II multi-objective optimization<br />model and game theory is suggested in order to find the optimum features of detention rockfill<br />dams. The proposed model is on the basis of the multi-objective genetic algorithm model (NSGA-<br />ΙΙ) and the multilayer perceptron neural network meta-model (MLP). The MLP meta-model<br />simulates the relationship between desig https://water-soil.tabrizu.ac.ir/article_5345_749547ce6e787f66f5a28ba3d68dc23e.pdf