Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/44993
Title: Solving the traveling salesman problem using genetic algorithm on Nvidia Cuda GPU
Authors: Quang, Mau Bach.
Keywords: DRNTU::Engineering::Computer science and engineering::Theory of computation::Analysis of algorithms and problem complexity
Issue Date: 2011
Abstract: The Traveling Salesman Problem (TSP) is one of the most intensively studied problems in computational mathematics. TSP has been used as a benchmark for many new algorithm ideas and optimization methods. Exact method for solving TSP, which has practically acceptable running time, has not been found. Therefore, various heuristics and approximation algorithms, which quickly yield good solutions, have been devised. Among those algorithms, the Genetic Algorithm (GA), modeled after the process of natural evolution, can be quickly implemented and deployed. However, GA does not utilize explicitly the knowledge of the problem on searching for the solutions. Consequently, hybrid methods that combine GA with other local search techniques have been attempted.
URI: http://hdl.handle.net/10356/44993
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
SCE10-0259.pdf
  Restricted Access
4.65 MBAdobe PDFView/Open

Page view(s)

767
checked on Sep 28, 2020

Download(s)

21
checked on Sep 28, 2020

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.