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Optimal Design of Aquifer Cleanup Systems Under Uncertainty using a Neural Network and a Genetic Algorithm
Utah State University Research Foundation, Logan
Department of Biological and Irrigation Engineering, Utah State University, Logan
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; .
Citation: (1999), Optimal Design of Aquifer Cleanup Systems Under Uncertainty using a Neural Network and a Genetic Algorithm, Water Resour. Res., 35(8), 2523–2532.
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