Simulated tempering and mean field annealing for mapping to multicomputers. (c1996)

Includes bibliographical references.

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Main Author: Aghazarian, Gabriel I. (author)
Format: masterThesis
Published: 1996
Subjects:
Online Access:http://hdl.handle.net/10725/347
https://doi.org/10.26756/th.1996.15
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author Aghazarian, Gabriel I.
author_facet Aghazarian, Gabriel I.
author_role author
dc.creator.none.fl_str_mv Aghazarian, Gabriel I.
dc.date.none.fl_str_mv 1996
1996-06
2011-04-11T08:18:17Z
2011-04-11T08:18:17Z
2011-04-11
dc.identifier.none.fl_str_mv http://hdl.handle.net/10725/347
https://doi.org/10.26756/th.1996.15
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Lebanese American University
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Neural networks (Computer science)
Simulated annealing (Mathematics)
Genetic algorithms
Combinatorial optimization
dc.title.none.fl_str_mv Simulated tempering and mean field annealing for mapping to multicomputers. (c1996)
dc.type.none.fl_str_mv Thesis
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/masterThesis
description Includes bibliographical references.
eu_rights_str_mv openAccess
format masterThesis
id LAURepo_a9fc6b718f0f6f9c5b9739bccbc43f32
language_invalid_str_mv en
network_acronym_str LAURepo
network_name_str Lebanese American University repository
oai_identifier_str oai:laur.lau.edu.lb:10725/347
publishDate 1996
publisher.none.fl_str_mv Lebanese American University
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Simulated tempering and mean field annealing for mapping to multicomputers. (c1996)Aghazarian, Gabriel I.Neural networks (Computer science)Simulated annealing (Mathematics)Genetic algorithmsCombinatorial optimizationIncludes bibliographical references.We worked on two physical optimization algorithms, Mean Field Annealing and Simulated Tempering, to solve the data mapping problem on multicomputers. We studied the effects of user defined parameters on MFA's behavior. These experiments resulted in recommending values to these parameters. Next, we implemented, for the first time, Simulated Tempering to solve the mapping problem. Then, we applied Mean Field Annealing, Simulated Tempering together with Simulated Annealing, Genetic Algorithm and Neural Network on randomly generated graphs. It was found that Neural Network (NN) proved to be the fastest algorithm although the quality of its solution is inferior to that of the Genetic Algorithm (GA), which was superior to all algorithms. Simulated Annealing had the second rank for both execution time and solution quality.1 bound copy: 44, [3] leaves; ill.; 30 cm. available at RNL.Lebanese American University2011-04-11T08:18:17Z2011-04-11T08:18:17Z19962011-04-111996-06Thesisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/10725/347https://doi.org/10.26756/th.1996.15eninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/3472020-05-18T14:53:44Z
spellingShingle Simulated tempering and mean field annealing for mapping to multicomputers. (c1996)
Aghazarian, Gabriel I.
Neural networks (Computer science)
Simulated annealing (Mathematics)
Genetic algorithms
Combinatorial optimization
status_str publishedVersion
title Simulated tempering and mean field annealing for mapping to multicomputers. (c1996)
title_full Simulated tempering and mean field annealing for mapping to multicomputers. (c1996)
title_fullStr Simulated tempering and mean field annealing for mapping to multicomputers. (c1996)
title_full_unstemmed Simulated tempering and mean field annealing for mapping to multicomputers. (c1996)
title_short Simulated tempering and mean field annealing for mapping to multicomputers. (c1996)
title_sort Simulated tempering and mean field annealing for mapping to multicomputers. (c1996)
topic Neural networks (Computer science)
Simulated annealing (Mathematics)
Genetic algorithms
Combinatorial optimization
url http://hdl.handle.net/10725/347
https://doi.org/10.26756/th.1996.15