Optimal Design of Aquifer Cleanup Systems Under Uncertainty using a Neural Network and a Genetic Algorithm

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Read Full Article Cited by WATER RESOURCES RESEARCH, VOL. 35, NO. 8, PAGES 2523–2532, 1999 Optimal Design of Aquifer Cleanup Systems Under Uncertainty using a Neural Network and a Genetic Algorithm Alaa H. Aly Utah State University Research Foundation, Logan Richard C. Peralta Department of Biological and Irrigation Engineering, Utah State University, Logan Abstract We present a methodology to account for the stochastic nature of hydraulic conductivity during the design of pump-and-treat systems for aquifer cleanup. The methodology (1) uses a genetic algorithm to find the global optimal solution and (2) incorporates a neural network to model the response surface within the genetic algorithm. We apply the methodology for a real example and different optimization scenarios. The employed optimization formulation requires few hydraulic conductivity realizations. The presented approach produces a trade-off curve between reliability and treatment facility size. Received 2 September 1998; accepted 14 July 1998. Read Full Article Cited by Citation: Aly, A. H., and R. C. Peralta (1999), Optimal Design of Aquifer Cleanup Systems Under Uncertainty using a Neural Network and a Genetic Algorithm, Water Resour. Res., 35(8), 2523–2532. Copyright 1999 by the American Geophysical Union.