Optimal Design of Remediation Systems

Using Progressive Genetic Algorithms

Dr. Mustafa M. Aral and Dr. Jiabao Guan
Multimedia Environmental Simulations Laboratory
School of Civil and Environmental Engineering
Georgia Institute of Technology
Atlanta, Georgia 30332

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The design of pump-and-treat groundwater remediation system was formulated as an optimization problem. The objective function in the formulation is to minimize the total cost of the pump-and-treat system, while defining the locations and extraction or injection rates of the candidate pumping wells as continuous decision variables. With this choice, the degree of freedom added to the optimization problem yields significant improvements on the solution. In this approach coupled solution of groundwater simulation models and optimization algorithms are required. The repeated use of the groundwater simulation models throughout the optimization cycle tend to be numerically complex and computationally costly when the governing equations are nonlinear. To overcome this drawback, we propose a new computational procedure, identified as progressive genetic algorithm (PGA), to solve the optimal design problem. PGA is a subdomain method, which combines standard genetic algorithm with groundwater simulation models and provides a powerful tool for the solution of highly nonlinear optimization problems. Numerical examples in a randomly heterogeneous aquifer are included to demonstrate the feasibility and efficiency of the proposed algorithm. Applications indicate that the proposed approach provides a feasible alternative for the solution of nonlinear optimization problems in groundwater management.

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