Date of Award

2020

Publisher

North Dakota State University

Document Type

Master's Paper

Degree Awarded

Master of Science (MS)

Program

Computer Science

Department

Computer Science

College

Engineering

Faculty Advisor

Ludwig, Simone

Description

Traveling salesman problem aims to find the shortest route. A salesman travels to each of the cities once. Genetic Algorithm is used for solving this problem, which returns the best solution found showing the distance that can be covered with the minimum cost (shortest path). A Spark-enabled parallel implementation was investigated in terms of performance. The aim of the study was to show the effect of parallelization of a Genetic Algorithm applied to the Travelling salesman problem. Experiments are run using different numbers of processors and the performance of the algorithm is evaluated based on the execution speed. To identify the best performing number of processors to be used, we made a comparison measuring the execution time of the algorithm for different numbers of cities using different numbers of cores.

Rights

NDSU policy 190.6.2

Rights Link

https://www.ndsu.edu/fileadmin/policy/190.pdf

Handle Identifier

https://hdl.handle.net/10365/31495

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