Computing non-dominated solutions in MOLFP

Detalhes bibliográficos
Autor(a) principal: Costa, João Paulo
Data de Publicação: 2007
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/5486
https://doi.org/10.1016/j.ejor.2005.11.051
Resumo: In this paper we present a technique to compute the maximum of a weighted sum of the objective functions in multiple objective linear fractional programming (MOLFP). The basic idea of the technique is to divide (by the approximate [`]middle') the non-dominated region in two sub-regions and to analyze each of them in order to discard one if it can be proved that the maximum of the weighted sum is in the other. The process is repeated with the remaining region. The process will end when the remaining regions are so little that the differences among their non-dominated solutions are lower than a pre-defined error. Through the discarded regions it is possible to extract conditions that establish weight indifference regions. These conditions define the variation range of the weights that necessarily leads to the same non-dominated solution. An example, illustrating the concept, is presented. Some computational results indicating the performance of the technique are also presented.
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spelling Computing non-dominated solutions in MOLFPMultiobjective linear fractional programmingSum of linear ratiosWeight indifference regionsIn this paper we present a technique to compute the maximum of a weighted sum of the objective functions in multiple objective linear fractional programming (MOLFP). The basic idea of the technique is to divide (by the approximate [`]middle') the non-dominated region in two sub-regions and to analyze each of them in order to discard one if it can be proved that the maximum of the weighted sum is in the other. The process is repeated with the remaining region. The process will end when the remaining regions are so little that the differences among their non-dominated solutions are lower than a pre-defined error. Through the discarded regions it is possible to extract conditions that establish weight indifference regions. These conditions define the variation range of the weights that necessarily leads to the same non-dominated solution. An example, illustrating the concept, is presented. Some computational results indicating the performance of the technique are also presented.http://www.sciencedirect.com/science/article/B6VCT-4JYKKS8-5/1/13ee9420d668c003ca28b4f8605de94a2007info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleaplication/PDFhttp://hdl.handle.net/10316/5486http://hdl.handle.net/10316/5486https://doi.org/10.1016/j.ejor.2005.11.051engEuropean Journal of Operational Research. 181:3 (2007) 1464-1475Costa, João Pauloinfo: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:RCAAP2020-11-06T16:49:00Zoai:estudogeral.uc.pt:10316/5486Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:45:38.570660Repositório 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 Computing non-dominated solutions in MOLFP
title Computing non-dominated solutions in MOLFP
spellingShingle Computing non-dominated solutions in MOLFP
Costa, João Paulo
Multiobjective linear fractional programming
Sum of linear ratios
Weight indifference regions
title_short Computing non-dominated solutions in MOLFP
title_full Computing non-dominated solutions in MOLFP
title_fullStr Computing non-dominated solutions in MOLFP
title_full_unstemmed Computing non-dominated solutions in MOLFP
title_sort Computing non-dominated solutions in MOLFP
author Costa, João Paulo
author_facet Costa, João Paulo
author_role author
dc.contributor.author.fl_str_mv Costa, João Paulo
dc.subject.por.fl_str_mv Multiobjective linear fractional programming
Sum of linear ratios
Weight indifference regions
topic Multiobjective linear fractional programming
Sum of linear ratios
Weight indifference regions
description In this paper we present a technique to compute the maximum of a weighted sum of the objective functions in multiple objective linear fractional programming (MOLFP). The basic idea of the technique is to divide (by the approximate [`]middle') the non-dominated region in two sub-regions and to analyze each of them in order to discard one if it can be proved that the maximum of the weighted sum is in the other. The process is repeated with the remaining region. The process will end when the remaining regions are so little that the differences among their non-dominated solutions are lower than a pre-defined error. Through the discarded regions it is possible to extract conditions that establish weight indifference regions. These conditions define the variation range of the weights that necessarily leads to the same non-dominated solution. An example, illustrating the concept, is presented. Some computational results indicating the performance of the technique are also presented.
publishDate 2007
dc.date.none.fl_str_mv 2007
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/5486
http://hdl.handle.net/10316/5486
https://doi.org/10.1016/j.ejor.2005.11.051
url http://hdl.handle.net/10316/5486
https://doi.org/10.1016/j.ejor.2005.11.051
dc.language.iso.fl_str_mv eng
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dc.relation.none.fl_str_mv European Journal of Operational Research. 181:3 (2007) 1464-1475
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