Origami toolkit: metaheuristic framework for combinatorial optimization problems: a machine learning tool for problem-solving and decision-making
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Data de Publicação: | 2020 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/104286 |
Resumo: | Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics |
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Origami toolkit: metaheuristic framework for combinatorial optimization problems: a machine learning tool for problem-solving and decision-makingMetaheuristicMetaheuristic FrameworkMachine LearningSoftware FrameworkProblem-solvingCombinatorial Optimization ProblemProblem formulationDissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsThe optimization of real-world problems is a challenging activity, difficult to be formulated and solved. Metaheuristics are recognized as powerful "optimization problem" solvers, and sometimes they are the only feasible approach. Metaheuristics are general heuristic that works in a meta-level - which can be applied to a wide variety of optimization problems. Metaheuristics can be accommodated to include problem specificities. However, these inclusions require a set of efforts to adapt the metaheuristic algorithm for a determined problem. In this master thesis, it will be researched and explored alternatives to develop a metaheuristic framework. Consequently, putting the metaheuristics on a higher level of abstraction. With this in mind, the framework is an approach to eliminate the necessity to adapt the metaheuristic to the problem peculiarities. Moreover, it also considers defining a standardization for problem formulation and object creation.Castelli, MauroVanneschi, LeonardoRUNPeres, Fernando Augusto Junqueira2022-07-27T00:30:29Z2020-07-292020-07-29T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/104286TID:202519279enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:49:49Zoai:run.unl.pt:10362/104286Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:40:12.140856Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Origami toolkit: metaheuristic framework for combinatorial optimization problems: a machine learning tool for problem-solving and decision-making |
title |
Origami toolkit: metaheuristic framework for combinatorial optimization problems: a machine learning tool for problem-solving and decision-making |
spellingShingle |
Origami toolkit: metaheuristic framework for combinatorial optimization problems: a machine learning tool for problem-solving and decision-making Peres, Fernando Augusto Junqueira Metaheuristic Metaheuristic Framework Machine Learning Software Framework Problem-solving Combinatorial Optimization Problem Problem formulation |
title_short |
Origami toolkit: metaheuristic framework for combinatorial optimization problems: a machine learning tool for problem-solving and decision-making |
title_full |
Origami toolkit: metaheuristic framework for combinatorial optimization problems: a machine learning tool for problem-solving and decision-making |
title_fullStr |
Origami toolkit: metaheuristic framework for combinatorial optimization problems: a machine learning tool for problem-solving and decision-making |
title_full_unstemmed |
Origami toolkit: metaheuristic framework for combinatorial optimization problems: a machine learning tool for problem-solving and decision-making |
title_sort |
Origami toolkit: metaheuristic framework for combinatorial optimization problems: a machine learning tool for problem-solving and decision-making |
author |
Peres, Fernando Augusto Junqueira |
author_facet |
Peres, Fernando Augusto Junqueira |
author_role |
author |
dc.contributor.none.fl_str_mv |
Castelli, Mauro Vanneschi, Leonardo RUN |
dc.contributor.author.fl_str_mv |
Peres, Fernando Augusto Junqueira |
dc.subject.por.fl_str_mv |
Metaheuristic Metaheuristic Framework Machine Learning Software Framework Problem-solving Combinatorial Optimization Problem Problem formulation |
topic |
Metaheuristic Metaheuristic Framework Machine Learning Software Framework Problem-solving Combinatorial Optimization Problem Problem formulation |
description |
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-07-29 2020-07-29T00:00:00Z 2022-07-27T00:30:29Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/104286 TID:202519279 |
url |
http://hdl.handle.net/10362/104286 |
identifier_str_mv |
TID:202519279 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799138017378566144 |