A new exact method for linear bilevel problems with multiple objective functions at the lower level
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Texto Completo: | https://hdl.handle.net/10316/99209 https://doi.org/10.1016/j.ejor.2022.02.047 |
Resumo: | In this paper we consider linear bilevel programming problems with multiple objective functions at the lower level. We propose a general-purpose exact method to compute the optimistic optimal solution, which is based on the search of efficient extreme solutions of an associated multiobjective linear problem with many objective functions. We also explore a heuristic procedure relying on the same principles. Although this procedure cannot ensure the global optimal solution but just a local optimum, it has shown to be quite effective in problems where the global optimum is difficult to obtain within a reasonable timeframe. A computational study is presented to evaluate the performance of the exact method and the heuristic procedure, comparing them with an exact and an approximate method proposed by other authors, using randomly generated instances. Our approach reveals interesting results in problems with few upper-level variables. |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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https://opendoar.ac.uk/repository/7160 |
spelling |
A new exact method for linear bilevel problems with multiple objective functions at the lower levelMultiple objective programmingLinear bilevel optimizationSemivectorial bilevel problemMultiobjective simplex methodIn this paper we consider linear bilevel programming problems with multiple objective functions at the lower level. We propose a general-purpose exact method to compute the optimistic optimal solution, which is based on the search of efficient extreme solutions of an associated multiobjective linear problem with many objective functions. We also explore a heuristic procedure relying on the same principles. Although this procedure cannot ensure the global optimal solution but just a local optimum, it has shown to be quite effective in problems where the global optimum is difficult to obtain within a reasonable timeframe. A computational study is presented to evaluate the performance of the exact method and the heuristic procedure, comparing them with an exact and an approximate method proposed by other authors, using randomly generated instances. Our approach reveals interesting results in problems with few upper-level variables.Elsevier2022-02info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://hdl.handle.net/10316/99209https://hdl.handle.net/10316/99209https://doi.org/10.1016/j.ejor.2022.02.047eng0377-22171872-6860https://doi.org/10.1016/j.ejor.2022.02.047Alves, M. JoãoAntunes, Carlos Henggelerinfo: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:RCAAP2025-03-25T12:06:05Zoai:estudogeral.uc.pt:10316/99209Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T05:48:15.772540Repositórios 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 |
A new exact method for linear bilevel problems with multiple objective functions at the lower level |
title |
A new exact method for linear bilevel problems with multiple objective functions at the lower level |
spellingShingle |
A new exact method for linear bilevel problems with multiple objective functions at the lower level Alves, M. João Multiple objective programming Linear bilevel optimization Semivectorial bilevel problem Multiobjective simplex method |
title_short |
A new exact method for linear bilevel problems with multiple objective functions at the lower level |
title_full |
A new exact method for linear bilevel problems with multiple objective functions at the lower level |
title_fullStr |
A new exact method for linear bilevel problems with multiple objective functions at the lower level |
title_full_unstemmed |
A new exact method for linear bilevel problems with multiple objective functions at the lower level |
title_sort |
A new exact method for linear bilevel problems with multiple objective functions at the lower level |
author |
Alves, M. João |
author_facet |
Alves, M. João Antunes, Carlos Henggeler |
author_role |
author |
author2 |
Antunes, Carlos Henggeler |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Alves, M. João Antunes, Carlos Henggeler |
dc.subject.por.fl_str_mv |
Multiple objective programming Linear bilevel optimization Semivectorial bilevel problem Multiobjective simplex method |
topic |
Multiple objective programming Linear bilevel optimization Semivectorial bilevel problem Multiobjective simplex method |
description |
In this paper we consider linear bilevel programming problems with multiple objective functions at the lower level. We propose a general-purpose exact method to compute the optimistic optimal solution, which is based on the search of efficient extreme solutions of an associated multiobjective linear problem with many objective functions. We also explore a heuristic procedure relying on the same principles. Although this procedure cannot ensure the global optimal solution but just a local optimum, it has shown to be quite effective in problems where the global optimum is difficult to obtain within a reasonable timeframe. A computational study is presented to evaluate the performance of the exact method and the heuristic procedure, comparing them with an exact and an approximate method proposed by other authors, using randomly generated instances. Our approach reveals interesting results in problems with few upper-level variables. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-02 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10316/99209 https://hdl.handle.net/10316/99209 https://doi.org/10.1016/j.ejor.2022.02.047 |
url |
https://hdl.handle.net/10316/99209 https://doi.org/10.1016/j.ejor.2022.02.047 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0377-2217 1872-6860 https://doi.org/10.1016/j.ejor.2022.02.047 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
instname_str |
FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
collection |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository.name.fl_str_mv |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
repository.mail.fl_str_mv |
info@rcaap.pt |
_version_ |
1833602477936607232 |