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Date of Award
Thesis-ISU Access Only
Master of Science (MS)
Department of Mathematics
We study engineered genetic algorithm (EGA), which is a self-optimizing, robust and stable optimization tool that operates under complicated modeling settings. The self-optimization feature of EGA improves the efficiency of the algorithm performance by implementing simulated annealing principles to genetic algorithm (GA) itself. An application has been considered using several compartmental models for modeling cholera epidemics in Haiti in 2010.
Chubarova, Irina Nikolayevna, "Modeling Cholera Using Engineered Genetic Algorithm" (2015). Theses and Dissertations. 374.