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Optimal design of aquifer cleanup systems under uncertainty using a neural network and a genetic algorithm
Author(s) -
Aly Alaa H.,
Peralta Richard C.
Publication year - 1999
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/98wr02368
Subject(s) - genetic algorithm , artificial neural network , reliability (semiconductor) , aquifer , hydraulic conductivity , optimal design , mathematical optimization , computer science , algorithm , groundwater , environmental science , engineering , mathematics , soil science , geotechnical engineering , machine learning , power (physics) , physics , quantum mechanics , soil water
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.