The cost of remediating contaminated groundwater systems is high given the transport limitations, the magnitude of the contaminated area, and the time-scale of the clean-up process. It is possible to replace trial-and-error remediation design with a mathematical optimization algorithm to determine the most cost-effective policy, resulting in potentially large cost savings. The analyst may utilize an optimization approach to explore the trade-offs between optimal remediation costs and remediation efficiency. The work utilizes a genetic algorithm to explore the sensitivity of optimal costs for in situ bioremediation given the ultimate in situ groundwater quality goals. The cost sensitivity to the remediation water quality goals will be evaluated for both static and dynamic problems.

Chan Hilton, A. B. and T. B. Culver. Groundwater bioremediation optimization using genetic algorithms. Water Resources and the Urban Environment. Proceedings of the 25th annual conference on water resources planning and management (E. D. Loucks, ed.), June 6-10, 1998, Chicago, IL: ASCE, 1998.