PROJECT SCHEDULING OPTIMIZATION IN ELECTRICAL POWER UTILITIES

Detalhes bibliográficos
Autor(a) principal: Mira,Cleber
Data de Publicação: 2015
Outros Autores: Viadanna,Paulo R., Souza,Maria Angélica, Moura,Arnaldo, Meidanis,João, Lima,Gabriel A. Costa, Bossolan,Renato P.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa operacional (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382015000200285
Resumo: The problem of choosing from a set of projects which ones should be executed and whenthey should start, depending on several restrictions involving project costs, risks, limited resources, dependencies among projects, and aiming at different, even conflicting, goals is known as the project portfolio selection (PPS) problem. We study a particular version of the PPS problem stemming from the operation of a real power generation company. It includes distinct categories of resources, intricate dependencies between projects, which are especially important for the management of power plants, and the prevention of risks. We present an algorithm based on the GRASP meta-heuristic for finding better results thanmanual solutions produced by specialists. The algorithm yielded solutions that decreased the risk by 47%, as measured by the company's standard methodology.
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spelling PROJECT SCHEDULING OPTIMIZATION IN ELECTRICAL POWER UTILITIESproject portfolio managementpower generationoptimizationschedulingThe problem of choosing from a set of projects which ones should be executed and whenthey should start, depending on several restrictions involving project costs, risks, limited resources, dependencies among projects, and aiming at different, even conflicting, goals is known as the project portfolio selection (PPS) problem. We study a particular version of the PPS problem stemming from the operation of a real power generation company. It includes distinct categories of resources, intricate dependencies between projects, which are especially important for the management of power plants, and the prevention of risks. We present an algorithm based on the GRASP meta-heuristic for finding better results thanmanual solutions produced by specialists. The algorithm yielded solutions that decreased the risk by 47%, as measured by the company's standard methodology.Sociedade Brasileira de Pesquisa Operacional2015-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382015000200285Pesquisa Operacional v.35 n.2 2015reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/0101-7438.2015.035.02.0285info:eu-repo/semantics/openAccessMira,CleberViadanna,Paulo R.Souza,Maria AngélicaMoura,ArnaldoMeidanis,JoãoLima,Gabriel A. CostaBossolan,Renato P.eng2015-07-27T00:00:00Zoai:scielo:S0101-74382015000200285Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2015-07-27T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false
dc.title.none.fl_str_mv PROJECT SCHEDULING OPTIMIZATION IN ELECTRICAL POWER UTILITIES
title PROJECT SCHEDULING OPTIMIZATION IN ELECTRICAL POWER UTILITIES
spellingShingle PROJECT SCHEDULING OPTIMIZATION IN ELECTRICAL POWER UTILITIES
Mira,Cleber
project portfolio management
power generation
optimization
scheduling
title_short PROJECT SCHEDULING OPTIMIZATION IN ELECTRICAL POWER UTILITIES
title_full PROJECT SCHEDULING OPTIMIZATION IN ELECTRICAL POWER UTILITIES
title_fullStr PROJECT SCHEDULING OPTIMIZATION IN ELECTRICAL POWER UTILITIES
title_full_unstemmed PROJECT SCHEDULING OPTIMIZATION IN ELECTRICAL POWER UTILITIES
title_sort PROJECT SCHEDULING OPTIMIZATION IN ELECTRICAL POWER UTILITIES
author Mira,Cleber
author_facet Mira,Cleber
Viadanna,Paulo R.
Souza,Maria Angélica
Moura,Arnaldo
Meidanis,João
Lima,Gabriel A. Costa
Bossolan,Renato P.
author_role author
author2 Viadanna,Paulo R.
Souza,Maria Angélica
Moura,Arnaldo
Meidanis,João
Lima,Gabriel A. Costa
Bossolan,Renato P.
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Mira,Cleber
Viadanna,Paulo R.
Souza,Maria Angélica
Moura,Arnaldo
Meidanis,João
Lima,Gabriel A. Costa
Bossolan,Renato P.
dc.subject.por.fl_str_mv project portfolio management
power generation
optimization
scheduling
topic project portfolio management
power generation
optimization
scheduling
description The problem of choosing from a set of projects which ones should be executed and whenthey should start, depending on several restrictions involving project costs, risks, limited resources, dependencies among projects, and aiming at different, even conflicting, goals is known as the project portfolio selection (PPS) problem. We study a particular version of the PPS problem stemming from the operation of a real power generation company. It includes distinct categories of resources, intricate dependencies between projects, which are especially important for the management of power plants, and the prevention of risks. We present an algorithm based on the GRASP meta-heuristic for finding better results thanmanual solutions produced by specialists. The algorithm yielded solutions that decreased the risk by 47%, as measured by the company's standard methodology.
publishDate 2015
dc.date.none.fl_str_mv 2015-08-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382015000200285
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382015000200285
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0101-7438.2015.035.02.0285
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
dc.source.none.fl_str_mv Pesquisa Operacional v.35 n.2 2015
reponame:Pesquisa operacional (Online)
instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron:SOBRAPO
instname_str Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron_str SOBRAPO
institution SOBRAPO
reponame_str Pesquisa operacional (Online)
collection Pesquisa operacional (Online)
repository.name.fl_str_mv Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
repository.mail.fl_str_mv ||sobrapo@sobrapo.org.br
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