Award Date

1-1-2003

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Committee Member

Wolfgang Bein

Number of Pages

102

Abstract

The central issue in creating new genetic algorithms is the algorithm's crossover method. My focus is on a particular crossover known as the Edge Assembly Crossover, or EAX, by Nagata and Kobayashi. The basics of a what make up a genetic algorithm is reviewed. The traveling salesman problem is defined. The EAX as an algorithm within an algorithm is explained. The crossover's implementation is original and is listed. The use of the graphic user interface, TSP View, used to run algorithms is explained as well as the extensions to the interface that were implemented for this study. The results of running a genetic algorithm using the EAX against traveling salesman problems, with a focus on ATT532, is discussed and compared to runs using other optimization algorithms. The question of why EAX works is addressed with conjectures for a possible future research path.

Keywords

Algorithms; Assembly; Crossover; Edge; Genetic; Problem; Salesman; Traveling

Controlled Subject

Computer science

File Format

pdf

File Size

4812.8 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Permissions

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Identifier

https://doi.org/10.25669/sm98-fs32


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