NDLI: Parallel real-valued genetic algorithms for bioremediation optimization of TCE-contaminated groundwater

Content Provider	IEEE Xplore Digital Library
Author	Garrett, C.A. Junqi Huang Goltz, M.N. Lamont, G.B.
Copyright Year	1999
Description	Author affiliation: Inst. of Technol., Wright-Patterson AFB, OH, USA (Garrett, C.A.)
Abstract	Remediation of groundwater contamination remediation can involve very expensive processes. A recent field evaluation of in situ aerobic cometabolic bioremediation demonstrated that this in situ (meaning "in place") technology has promise as an inexpensive and effective alternative to current technologies for the remediation of trichloroethylene (TCE)-contaminated groundwater. A mathematical fate and transport model has been developed to simulate the relevant physical, chemical, and biological processes that affect TCE fate and transport during the application of in situ bioremediation. In order to cost-effectively implement the technology developers must understand how to adjust engineered parameters in order to optimize system performance. While the fate and transport model can provide system performance information, the complexity of the system and the number of engineered parameters that can be varied make determining an optimal design problematic. Thus, real-valued genetic algorithms are used to determine those design parameter values that attempt to optimize the performance of this complex treatment system. In augmenting the remediation objective function with time-varying penalty weights associated with the model constraints, "acceptable" design parameter values were obtained. By executing the genetic algorithm in parallel using a "farming model" on an efficient parallel computational platform with MPI, we were able to obtain reasonable run times.
File Size	722130
File Format	PDF
ISBN	0780355369
DOI	10.1109/CEC.1999.785546
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-07-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic algorithms Chemical technology Biological system modeling System performance Contamination Mathematical model Chemical processes Biological processes Design engineering Algorithm design and analysis
Content Type	Text
Resource Type	Article

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