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Graduation Term
2015
Degree Name
Master of Science (MS)
Department
Department of Mathematics
Committee Chair
Olcay Akman
Abstract
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.
Access Type
Thesis-ISU Access Only
Recommended Citation
Chubarova, Irina Nikolayevna, "Modeling Cholera Using Engineered Genetic Algorithm" (2015). Theses and Dissertations. 374.
https://ir.library.illinoisstate.edu/etd/374
DOI
http://doi.org/10.30707/ETD2015.Chubarova.I