Genetic Algorithms for Optimal Operation of Soil Aquifer Treatment Systems

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Abstract

The genetic algorithm (GA) is a nonconventional search technique which is patterned after the biological processes of natural selection and evolution. It has the ability to search large and complex decision spaces and handle nonconvexities. In this paper, the genetic algorithm is investigated and applied to solve the optimal operation problem of soil aquifer treatment (SAT) systems. This problem involves finding optimal water application time and drying time which maximize infiltration for a predetermined starting influent rate of waste water and subject to various physical and operational constraints. A new scaling method is developed and some improvements on the evolution procedure are presented. A comprehensive GA–SAT computer model was developed and applied to an example SAT problem. The results are encouraging, when compared with using the successive approximation linear quadratic regulator algorithm. It was found that genetic algorithms are easy to program and interface with large complicated simulators.

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