Threshold robustness in discrete facility location problems: a bi-objective approach

The two best studied facility location problems are the p-median problem and the uncapacitated facility location problem (Daskin, Network and discrete location: models, algorithms, and applications. Wiley, New York, 1995; Mirchandani and Francis, Discrete location theory. Wiley, New York, 1990). Bot...

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Detalles Bibliográficos
Autores: Carrizosa Priego, Emilio José, Ushakov, Anton, Vasilyev, Igor
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/107825
Acceso en línea:https://hdl.handle.net/11441/107825
https://doi.org/10.1007/s11590-015-0892-5
Access Level:acceso abierto
Palabra clave:Discrete facility location
Robustness
Bi-objective combinatorial optimization
p-median problem
UFLP
ε-Constraint method
δ-Dominating set
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spelling Threshold robustness in discrete facility location problems: a bi-objective approachCarrizosa Priego, Emilio JoséUshakov, AntonVasilyev, IgorDiscrete facility locationRobustnessBi-objective combinatorial optimizationp-median problemUFLPε-Constraint methodδ-Dominating setThe two best studied facility location problems are the p-median problem and the uncapacitated facility location problem (Daskin, Network and discrete location: models, algorithms, and applications. Wiley, New York, 1995; Mirchandani and Francis, Discrete location theory. Wiley, New York, 1990). Both seek the location of the facilities minimizing the total cost, assuming no uncertainty in costs exists, and thus all parameters are known. In most real-world location problems the demand is not certain, because it is a long-term planning decision, and thus, together with the minimization of costs, optimizing some robustness measure is sound. In this paper we address bi-objective versions of such location problems, in which the total cost, as well as the robustness associated with the demand, are optimized. A dominating set is constructed for these bi-objective nonlinear integer problems via the ε-constraint method. Computational results on test instances are presented, showing the feasibility of our approach to approximate the Pareto-optimal set.SpringerEstadística e Investigación OperativaFQM329: Optimización2015info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/107825https://doi.org/10.1007/s11590-015-0892-5reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésOptimization Letters, 9 (7), 1297-1314.https://doi.org/10.1007/s11590-015-0892-5info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1078252026-06-17T12:51:07Z
dc.title.none.fl_str_mv Threshold robustness in discrete facility location problems: a bi-objective approach
title Threshold robustness in discrete facility location problems: a bi-objective approach
spellingShingle Threshold robustness in discrete facility location problems: a bi-objective approach
Carrizosa Priego, Emilio José
Discrete facility location
Robustness
Bi-objective combinatorial optimization
p-median problem
UFLP
ε-Constraint method
δ-Dominating set
title_short Threshold robustness in discrete facility location problems: a bi-objective approach
title_full Threshold robustness in discrete facility location problems: a bi-objective approach
title_fullStr Threshold robustness in discrete facility location problems: a bi-objective approach
title_full_unstemmed Threshold robustness in discrete facility location problems: a bi-objective approach
title_sort Threshold robustness in discrete facility location problems: a bi-objective approach
dc.creator.none.fl_str_mv Carrizosa Priego, Emilio José
Ushakov, Anton
Vasilyev, Igor
author Carrizosa Priego, Emilio José
author_facet Carrizosa Priego, Emilio José
Ushakov, Anton
Vasilyev, Igor
author_role author
author2 Ushakov, Anton
Vasilyev, Igor
author2_role author
author
dc.contributor.none.fl_str_mv Estadística e Investigación Operativa
FQM329: Optimización
dc.subject.none.fl_str_mv Discrete facility location
Robustness
Bi-objective combinatorial optimization
p-median problem
UFLP
ε-Constraint method
δ-Dominating set
topic Discrete facility location
Robustness
Bi-objective combinatorial optimization
p-median problem
UFLP
ε-Constraint method
δ-Dominating set
description The two best studied facility location problems are the p-median problem and the uncapacitated facility location problem (Daskin, Network and discrete location: models, algorithms, and applications. Wiley, New York, 1995; Mirchandani and Francis, Discrete location theory. Wiley, New York, 1990). Both seek the location of the facilities minimizing the total cost, assuming no uncertainty in costs exists, and thus all parameters are known. In most real-world location problems the demand is not certain, because it is a long-term planning decision, and thus, together with the minimization of costs, optimizing some robustness measure is sound. In this paper we address bi-objective versions of such location problems, in which the total cost, as well as the robustness associated with the demand, are optimized. A dominating set is constructed for these bi-objective nonlinear integer problems via the ε-constraint method. Computational results on test instances are presented, showing the feasibility of our approach to approximate the Pareto-optimal set.
publishDate 2015
dc.date.none.fl_str_mv 2015
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/107825
https://doi.org/10.1007/s11590-015-0892-5
url https://hdl.handle.net/11441/107825
https://doi.org/10.1007/s11590-015-0892-5
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Optimization Letters, 9 (7), 1297-1314.
https://doi.org/10.1007/s11590-015-0892-5
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300719

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