Shortest path problems with partial information: Models and algorithms for detecting dominance

Detalhes bibliográficos
Autor(a) principal: Dias, Luís C.
Data de Publicação: 2000
Outros Autores: Clímaco, João N.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: https://hdl.handle.net/10316/5506
https://doi.org/10.1016/S0377-2217(99)00005-3
Resumo: In this work we focus on partial information models for the well-known shortest path problem, where we consider multiple instances of values for the parameters that determine the cost of each arc. This allows coping with the uncertainty about the future, the imprecision of data, the arbitrariness of some options, the evolving values of the decision makers (DMs) and/or the multiplicity of DMs (in group decision making). This paper proves some results and presents detailed algorithms to identify the set of non dominated paths, a concept from decision theory under partial information. We first address problems with a finite set of instances, then problems with a general (eventually not discrete) set of instances and finally we study a particular case of the latter, which complies with a condition that may hold in some situations. To deal with these partial information problems we propose a new use for existing multicriteria algorithms based on the ranking of shortest paths.
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spelling Shortest path problems with partial information: Models and algorithms for detecting dominanceNetwork programmingPartial informationMulticriteria analysisIn this work we focus on partial information models for the well-known shortest path problem, where we consider multiple instances of values for the parameters that determine the cost of each arc. This allows coping with the uncertainty about the future, the imprecision of data, the arbitrariness of some options, the evolving values of the decision makers (DMs) and/or the multiplicity of DMs (in group decision making). This paper proves some results and presents detailed algorithms to identify the set of non dominated paths, a concept from decision theory under partial information. We first address problems with a finite set of instances, then problems with a general (eventually not discrete) set of instances and finally we study a particular case of the latter, which complies with a condition that may hold in some situations. To deal with these partial information problems we propose a new use for existing multicriteria algorithms based on the ranking of shortest paths.http://www.sciencedirect.com/science/article/B6VCT-3Y9MCF4-2/1/08f0e5f69f786fbe024d2c68ad927ff12000info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleaplication/PDFhttps://hdl.handle.net/10316/5506https://hdl.handle.net/10316/5506https://doi.org/10.1016/S0377-2217(99)00005-3engEuropean Journal of Operational Research. 121:1 (2000) 16-31Dias, Luís C.Clímaco, João N.info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2020-11-06T16:59:50Zoai:estudogeral.uc.pt:10316/5506Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T04:58:20.793535Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Shortest path problems with partial information: Models and algorithms for detecting dominance
title Shortest path problems with partial information: Models and algorithms for detecting dominance
spellingShingle Shortest path problems with partial information: Models and algorithms for detecting dominance
Dias, Luís C.
Network programming
Partial information
Multicriteria analysis
title_short Shortest path problems with partial information: Models and algorithms for detecting dominance
title_full Shortest path problems with partial information: Models and algorithms for detecting dominance
title_fullStr Shortest path problems with partial information: Models and algorithms for detecting dominance
title_full_unstemmed Shortest path problems with partial information: Models and algorithms for detecting dominance
title_sort Shortest path problems with partial information: Models and algorithms for detecting dominance
author Dias, Luís C.
author_facet Dias, Luís C.
Clímaco, João N.
author_role author
author2 Clímaco, João N.
author2_role author
dc.contributor.author.fl_str_mv Dias, Luís C.
Clímaco, João N.
dc.subject.por.fl_str_mv Network programming
Partial information
Multicriteria analysis
topic Network programming
Partial information
Multicriteria analysis
description In this work we focus on partial information models for the well-known shortest path problem, where we consider multiple instances of values for the parameters that determine the cost of each arc. This allows coping with the uncertainty about the future, the imprecision of data, the arbitrariness of some options, the evolving values of the decision makers (DMs) and/or the multiplicity of DMs (in group decision making). This paper proves some results and presents detailed algorithms to identify the set of non dominated paths, a concept from decision theory under partial information. We first address problems with a finite set of instances, then problems with a general (eventually not discrete) set of instances and finally we study a particular case of the latter, which complies with a condition that may hold in some situations. To deal with these partial information problems we propose a new use for existing multicriteria algorithms based on the ranking of shortest paths.
publishDate 2000
dc.date.none.fl_str_mv 2000
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dc.identifier.uri.fl_str_mv https://hdl.handle.net/10316/5506
https://hdl.handle.net/10316/5506
https://doi.org/10.1016/S0377-2217(99)00005-3
url https://hdl.handle.net/10316/5506
https://doi.org/10.1016/S0377-2217(99)00005-3
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv European Journal of Operational Research. 121:1 (2000) 16-31
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