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Date of Award

3-22-2015

Document Type

Thesis and Dissertation-ISU Access Only

Degree Name

Master of Science (MS)

Department

Department of Mathematics

First Advisor

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.

Comments

Imported from ProQuest Chubarova_ilstu_0092N_10503.pdf

Page Count

94

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