Using specialized agents in a distributed MAS to solve airline operations problems: a case study

Detalhes bibliográficos
Autor(a) principal: António J. M. Castro
Data de Publicação: 2007
Outros Autores: Eugénio Oliveira
Tipo de documento: Livro
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/5353
Resumo: An airline schedule very rarely operates as planned. Problems related with aircrafts, crew members and passengers are common and the actions towards the solution of these problems are usually known as operations recovery. The Airline Operations Control Center (AOCC) tries to solve these problems with the minimum cost and satisfying all the required rules. In this paper we present the implementation of a Distributed Multi-Agent System (MAS) representing the existing roles in an AOCC. This MAS has several specialized software agents that implement different algorithms, competing to find the best solution for each problem. We present a real case study where a crew recovery problem is solved We show that it is possible to find valid solutions, in less time and with a smaller cost.
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spelling Using specialized agents in a distributed MAS to solve airline operations problems: a case studyInteligência artificialArtificial intelligenceAn airline schedule very rarely operates as planned. Problems related with aircrafts, crew members and passengers are common and the actions towards the solution of these problems are usually known as operations recovery. The Airline Operations Control Center (AOCC) tries to solve these problems with the minimum cost and satisfying all the required rules. In this paper we present the implementation of a Distributed Multi-Agent System (MAS) representing the existing roles in an AOCC. This MAS has several specialized software agents that implement different algorithms, competing to find the best solution for each problem. We present a real case study where a crew recovery problem is solved We show that it is possible to find valid solutions, in less time and with a smaller cost.20072007-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/5353eng10.1109/iat.2007.24António J. M. CastroEugénio Oliveirainfo: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:RCAAP2023-11-29T14:52:17Zoai:repositorio-aberto.up.pt:10216/5353Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:10:36.190069Repositório 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 Using specialized agents in a distributed MAS to solve airline operations problems: a case study
title Using specialized agents in a distributed MAS to solve airline operations problems: a case study
spellingShingle Using specialized agents in a distributed MAS to solve airline operations problems: a case study
António J. M. Castro
Inteligência artificial
Artificial intelligence
title_short Using specialized agents in a distributed MAS to solve airline operations problems: a case study
title_full Using specialized agents in a distributed MAS to solve airline operations problems: a case study
title_fullStr Using specialized agents in a distributed MAS to solve airline operations problems: a case study
title_full_unstemmed Using specialized agents in a distributed MAS to solve airline operations problems: a case study
title_sort Using specialized agents in a distributed MAS to solve airline operations problems: a case study
author António J. M. Castro
author_facet António J. M. Castro
Eugénio Oliveira
author_role author
author2 Eugénio Oliveira
author2_role author
dc.contributor.author.fl_str_mv António J. M. Castro
Eugénio Oliveira
dc.subject.por.fl_str_mv Inteligência artificial
Artificial intelligence
topic Inteligência artificial
Artificial intelligence
description An airline schedule very rarely operates as planned. Problems related with aircrafts, crew members and passengers are common and the actions towards the solution of these problems are usually known as operations recovery. The Airline Operations Control Center (AOCC) tries to solve these problems with the minimum cost and satisfying all the required rules. In this paper we present the implementation of a Distributed Multi-Agent System (MAS) representing the existing roles in an AOCC. This MAS has several specialized software agents that implement different algorithms, competing to find the best solution for each problem. We present a real case study where a crew recovery problem is solved We show that it is possible to find valid solutions, in less time and with a smaller cost.
publishDate 2007
dc.date.none.fl_str_mv 2007
2007-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/book
format book
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/10216/5353
url https://hdl.handle.net/10216/5353
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1109/iat.2007.24
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 reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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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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