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A Multi-objective Optimization Nested Evolutionary Algorithm for Locating Apoptotic Cellular Automata

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Title: A Multi-objective Optimization Nested Evolutionary Algorithm for Locating Apoptotic Cellular Automata
Author: Pugh, Carolyn
Department: Department of Mathematics and Statistics
Program: Mathematics and Statistics
Advisor: Ashlock, Daniel
Abstract: Real world decisions frequently involve the consideration of multiple, often conflicting, factors. These problems usually have more than one optimal solution. Multi-objective Optimization Evolutionary Algorithms attempt to solve such problems by finding as many optimal solutions as possible at one time. This thesis proposes a new nested algorithm, Multi-objective Optimization Nested Evolutionary Algorithm (MONEA), that aims to solve multi-objective optimization problems by breaking them down into single-objective optimization problems with a new type of function. It tests MONEA on two different problems and compares the results with a well known algorithm, NSGA-II. The first problem focuses on testing MONEA's abilities for a trivial set of solutions and the second serves as an advanced problem that has unknown solutions.
URI: http://hdl.handle.net/10214/8023
Date: 2014-04


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