2015
DOI: 10.1007/s10040-015-1297-3
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Preface: Optimization for groundwater characterization and management

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Cited by 16 publications
(11 citation statements)
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“…Linked optimization methodologies are widely used for characterization of unknown groundwater contaminated source, in terms of flux magnitude, location and activity history in contaminated aquifers [1] [2]. Transport of contaminants comprising of multiple chemically reactive species, in contaminated groundwater systems, is complex and highly non-linear process.…”
Section: Introductionmentioning
confidence: 99%
“…Linked optimization methodologies are widely used for characterization of unknown groundwater contaminated source, in terms of flux magnitude, location and activity history in contaminated aquifers [1] [2]. Transport of contaminants comprising of multiple chemically reactive species, in contaminated groundwater systems, is complex and highly non-linear process.…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, there is less limitation in mathematical definition of objective function and constraints compared to former optimization algorithms such as linear programming [22]. Finally, evolutionary algorithms can optimally identify relatively large number of decision variables [23], and utilization of the evolutionary optimization algorithms simplifies the linking process.…”
Section: Introductionmentioning
confidence: 99%
“…Examples of the evolutionary optimization algorithms include: genetic algorithm (GA) [24], tabu search (TS) [25], simulated annealing (SA), adaptive simulated annealing (ASA) [26], and differential evolution algorithm [27]. Yeh [28] and Datta and Kourakos [22] presented an overview on various optimization methods coupled with simulation techniques utilized for groundwater quantity management, and quality management, respectively.…”
Section: Introductionmentioning
confidence: 99%
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“…Therefore, replacing the numerical simulation models by surrogate models can result in very substantial computational efficiency and feasibility [28]. In the present study, an alternative approach to the linked simulation optimization model and SMBO for optimal characterization of unknown groundwater contaminant sources is proposed and evaluated for potential applicability.…”
Section: Introductionmentioning
confidence: 99%