Abstract—In the present paper, a multi objective
optimization approach based in Genetic Algorithm, Design Of
Experiments and Response Surface Method strategies, is
applied in order to predict the optimal CFD model parameters,
allowing to model with high accuracy the 3D free surface flow of
urban flood propagation retaining the total computation time
(CPU-time) as short as possible. An experimental data set was
used in this study as a validation means for numerical optimized
models. We can say that the constraints in terms of computation
time and accuracy, related to the application of 3D CFD
modeling for flood propagation problems can be overcome by
making an optimal choice of the advanced parameters of model.
Index Terms—Urban flood modeling, computational fluid
dynamics (CFD), multi objective optimization problems
(MOOP), genetic algorithm (GA), response surface method
(RSM), design of experiments (DOE).
M. Rezoug, R. E. Meouche and R. Hamzaoui are with the Institute of
Research on Constructibility –ESTP Paris, 28, avenue du Président Wilson -
94234 Cachan cedex, France (e-mail: rezoug@profs.estp.fr).
Z-Q. Feng is with the EVRY Laboratory of Mechanics and Power. Evry
University, 40 rue du Pelvoux, 91020 Evry, France.
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Cite:M. Rezoug, R. E. Meouche, R. Hamzaoui, and Z.-Q. Feng, "Using the Fast Multi-Objective Genetic Algorithm to
Improve the Urban Flood Modeling," International Journal of Engineering and Technology vol. 5, no. 3, pp. 341-344, 2013.
