Comparison of a genetic algorithm and mathematical programming to the design of groundwater cleanup systems
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چکیده
We present and apply a new simulation/optimization approach for singleand multiple-planning period problems in groundwater remediation. Instead of the traditional control locations for contaminant concentrations, \Ve use an LC>O 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.
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تاریخ انتشار 2017