Optimal groundwater remediation under uncertainty using multi-objective optimization
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A methodology is developed for optimal remediation of groundwater aquifers under
hydraulic conductivity uncertainty. A multi-objective management method, based on
pump-and-treat remediation technology, is proposed. The pumping rates and the well
locations are the decision variables and two objectives are chosen: minimization of
contaminated groundwater present in the aquifer and minimization of remediation
cost. A Monte Carlo simulation method is used to cope with hydraulic conductivity
uncertainty. A number of equally probable realizations of hydraulic conductivity
are created and a Pareto front is obtained using a modified multi-objective Genetic
Algorithm. A penalty function is utilized to maintain the algebraic sum of pumping
and recharging rates equal to zero. Since Monte Carlo simulation is CPU time
consuming, a method is proposed to identify the most critical realizations. A
Pareto front with an assigned probability can be derived, so that the decision
maker can make decisions of known reliability.