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Comparison of a Genetic Algorithm and Mathematical Programming to the Design of Groundwater Cleanup Systems
Utah State University Research Foundation, Logan
Department of Biological and Irrigation Engineering, Utah State University, Logan
We present and apply a new simulation/optimization approach for single- and multiple-planning period problems in groundwater remediation. Instead of the traditional control locations for contaminant concentrations, we use an L ∞ norm as a global measure of aquifer contamination (CMAX). We use response-surface constraints to represent CMAX within the optimization model. We compare the performance of formal mixed integer nonlinear programming and a genetic algorithm for several optimization scenarios.
Received 19 March 1998; accepted 23 December 1998; .
Citation: (1999), Comparison of a Genetic Algorithm and Mathematical Programming to the Design of Groundwater Cleanup Systems, Water Resour. Res., 35(8), 2415–2425.
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