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Title Elitist GA based evolutionary algorithm for groundwater contaminant remediation using rump and treat method
 
Names SHARIEF, SMV
ELDHO, TI
RASTOGI, AK
Date Issued 2008 (iso8601)
Abstract This paper presents the application of coupled simulation-optimization model using finite element method (FEM) and Elite genetic algorithm (EGA) for remediation of contaminated groundwater using the pump and treat method. The optimization of pump and treat remediation design using evolutionary algorithms requires that the flow and solute transport model is run repeatedly, in order to calculate the objective function associated with the possible design and to evaluate whether various hydraulic and concentration constraints are met. The model is applied to determine the minimum pumping rates needed to remediate an existing contaminant plume in a confined aquifer. In an elite genetic algorithm, the statistics of the population best solutions cannot degrade with generations. In the present study, the best 50 % of the population from the current population is directly copied to the next generation. The rest of the new population is created by usual genetic operations applied on the entire current population including the chosen %εelite members. In this way, the best solutions of the current population are not only getting passed from one generation to another, but they also participate with other members of the population in creating other population members. A hypothetical problem of solute mass transport in a confined aquifer is considered for the remediation of contaminated groundwater. The coupled FEM-EGA model has been applied for the decontamination of the hypothetical confined aquifer to demonstrate the effectiveness of the proposed technique. The study found that an optimal pumping policy for aquifer decontamination using pump and treat method can be established by applying the FEM-EGA model.
Genre Article
Topic Finite Element Simulation
Identifier Proceedings of the 12th IACMAG: Geomechanics in the Emerging Social & Technological Age, Goa, India, 1-6 October 2008, 2505-2512