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General Information
Editor-in-chief
Prof. T. Hikmet Karakoc
Anadolu University, Faculty of Aeronautics and Astronautics, Turkey

IJET 2013 Vol.5(3): 341-344 ISSN: 1793-8236
DOI: 10.7763/IJET.2013.V5.571

Using the Fast Multi-Objective Genetic Algorithm to Improve the Urban Flood Modeling

M. Rezoug, R. E. Meouche, R. Hamzaoui, and Z.-Q. Feng
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.

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