Solving airline operations problems using specialized agents in a distributed multi-agent system

Detalhes bibliográficos
Autor(a) principal: António J. M. Castro
Data de Publicação: 2008
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/10216/6720
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 deals with several operational bases and for each type of operation problems it has several specialized software agents that implement different algorithms (heuristic, AI, OR, etc.), competing to find the best solution for each problem. We present a real case study taken from an AOCC where a crew recovery problem is solved. Computational results using a real airline schedule are presented, including a comparison with a solution for the same problem found by the human operators in the AOCC. We show that, even in simple problems and when comparing with solutions found by human operators, it is possible to find valid solutions, in less time and with a smaller cost.
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spelling Solving airline operations problems using specialized agents in a distributed multi-agent systemInteligência artificial, Ciências da computação e da informaçãoArtificial intelligence, Computer and information sciencesAn 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 deals with several operational bases and for each type of operation problems it has several specialized software agents that implement different algorithms (heuristic, AI, OR, etc.), competing to find the best solution for each problem. We present a real case study taken from an AOCC where a crew recovery problem is solved. Computational results using a real airline schedule are presented, including a comparison with a solution for the same problem found by the human operators in the AOCC. We show that, even in simple problems and when comparing with solutions found by human operators, it is possible to find valid solutions, in less time and with a smaller cost.20082008-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/6720eng10.1007/978-3-540-88710-2_14António 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:RCAAP2023-11-29T14:05:11Zoai:repositorio-aberto.up.pt:10216/6720Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:54:24.299033Repositório 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 Solving airline operations problems using specialized agents in a distributed multi-agent system
title Solving airline operations problems using specialized agents in a distributed multi-agent system
spellingShingle Solving airline operations problems using specialized agents in a distributed multi-agent system
António J. M. Castro
Inteligência artificial, Ciências da computação e da informação
Artificial intelligence, Computer and information sciences
title_short Solving airline operations problems using specialized agents in a distributed multi-agent system
title_full Solving airline operations problems using specialized agents in a distributed multi-agent system
title_fullStr Solving airline operations problems using specialized agents in a distributed multi-agent system
title_full_unstemmed Solving airline operations problems using specialized agents in a distributed multi-agent system
title_sort Solving airline operations problems using specialized agents in a distributed multi-agent system
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, Ciências da computação e da informação
Artificial intelligence, Computer and information sciences
topic Inteligência artificial, Ciências da computação e da informação
Artificial intelligence, Computer and information sciences
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 deals with several operational bases and for each type of operation problems it has several specialized software agents that implement different algorithms (heuristic, AI, OR, etc.), competing to find the best solution for each problem. We present a real case study taken from an AOCC where a crew recovery problem is solved. Computational results using a real airline schedule are presented, including a comparison with a solution for the same problem found by the human operators in the AOCC. We show that, even in simple problems and when comparing with solutions found by human operators, it is possible to find valid solutions, in less time and with a smaller cost.
publishDate 2008
dc.date.none.fl_str_mv 2008
2008-01-01T00:00:00Z
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/10216/6720
url https://hdl.handle.net/10216/6720
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1007/978-3-540-88710-2_14
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dc.format.none.fl_str_mv application/pdf
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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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