Remediation of heterogeneous aquifers based on multiobjective optimization and adaptive determination of critical realizations

Kourakos, G; Mantoglou, A

dc.contributor.author	Kourakos, G	en
dc.contributor.author	Mantoglou, A	en
dc.date.accessioned	2014-03-01T01:29:05Z
dc.date.available	2014-03-01T01:29:05Z
dc.date.issued	2008	en
dc.identifier.issn	0043-1397	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/19121
dc.subject	multiobjective optimization	en
dc.subject.classification	Environmental Sciences	en
dc.subject.classification	Limnology	en
dc.subject.classification	Water Resources	en
dc.subject.other	Adaptive algorithms	en
dc.subject.other	Aquifers	en
dc.subject.other	Damping	en
dc.subject.other	Hydrogeology	en
dc.subject.other	Monte Carlo methods	en
dc.subject.other	Optimization	en
dc.subject.other	Pollution	en
dc.subject.other	Adaptive procedures	en
dc.subject.other	Automatic procedures	en
dc.subject.other	Clean-up costs	en
dc.subject.other	Computational burdens	en
dc.subject.other	Computer time	en
dc.subject.other	Genetic optimization algorithms	en
dc.subject.other	Heterogeneous aquifers	en
dc.subject.other	Initial designs	en
dc.subject.other	Loss of performance	en
dc.subject.other	Monte Carlo simulations	en
dc.subject.other	Multi objectives	en
dc.subject.other	Optimal solutions	en
dc.subject.other	Reliability levels	en
dc.subject.other	Safety thresholds	en
dc.subject.other	Similarity criterion	en
dc.subject.other	Step by steps	en
dc.subject.other	Stochastic simulations	en
dc.subject.other	Multiobjective optimization	en
dc.subject.other	aquifer	en
dc.subject.other	heterogeneity	en
dc.subject.other	hydraulic conductivity	en
dc.subject.other	Monte Carlo analysis	en
dc.subject.other	remediation	en
dc.title	Remediation of heterogeneous aquifers based on multiobjective optimization and adaptive determination of critical realizations	en
heal.type	journalArticle	en
heal.identifier.primary	10.1029/2008WR007108	en
heal.identifier.secondary	http://dx.doi.org/10.1029/2008WR007108	en
heal.identifier.secondary	W12408	en
heal.language	English	en
heal.publicationDate	2008	en
heal.abstract	A method for optimal remediation of heterogeneous aquifers based on stochastic simulation with adaptive determination of critical realizations is developed. Multiple hydraulic conductivity realizations are generated using the turning bands method while Monte Carlo simulation is incorporated into a multiobjective genetic optimization algorithm. In order to reduce the computational burden of Monte Carlo simulations, an adaptive procedure is developed for identifying ""critical realizations"" which are the ones that have an effect on the optimal solution depending on desired reliability level. The adaptive procedure is embedded into the genetic optimization algorithm where noncritical realizations are eliminated step by step during the advancement of optimization. When the number of remaining realizations reaches a minimum, some new realizations are added. The specific realizations which are removed or added in the critical set are selected by an automatic procedure controlled by a similarity criterion based on rankings of realizations. This is a significant improvement over the nonadaptive methodology for identification of critical realizations and does not require using a number of initial designs and a safety threshold. The methodology is applied in a remediation problem with two objectives (reduction of contaminant mass and cleanup cost). The applications indicate significant savings in computer time without loss of performance. Copyright 2008 by the American Geophysical Union.	en
heal.publisher	AMER GEOPHYSICAL UNION	en
heal.journalName	Water Resources Research	en
dc.identifier.doi	10.1029/2008WR007108	en
dc.identifier.isi	ISI:000261690900007	en
dc.identifier.volume	44	en
dc.identifier.issue	12	en