Minimum spanning trees with neighborhoods: mathematical programming formulations and solution methods

This paper studies Minimum Spanning Trees under incomplete information for its vertices. We assume that no information is available on the precise placement of vertices so that it is only known that vertices belong to some neighborhoods that are second order cone representable and distances are meas...

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Autores: Blanco Izquierdo, Víctor, Fernández Aréizaga, Elena, Puerto Albandoz, Justo
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2017
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/61450
Acceso en línea:http://hdl.handle.net/11441/61450
https://doi.org/10.1016/j.ejor.2017.04.023
Access Level:acceso abierto
Palabra clave:Minimum spanning trees
Neighborhoods
Mixed integer non linear programming
Second order cone programming
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spelling Minimum spanning trees with neighborhoods: mathematical programming formulations and solution methodsBlanco Izquierdo, VíctorFernández Aréizaga, ElenaPuerto Albandoz, JustoMinimum spanning treesNeighborhoodsMixed integer non linear programmingSecond order cone programmingThis paper studies Minimum Spanning Trees under incomplete information for its vertices. We assume that no information is available on the precise placement of vertices so that it is only known that vertices belong to some neighborhoods that are second order cone representable and distances are measured with a ℓq-norm. Two mixed integer non linear mathematical programming formulations are presented, based on alternative representations of subtour elimination constraints. A solution scheme is also proposed, resulting from a reformulation suitable for a Benders-like decomposition, which is embedded within an exact branch-and-cut framework. Furthermore, a mathheuristic is developed, which alternates in solving convex subproblems in different solution spaces, and is able to solve larger instances. The results of extensive computational experiments are reported and analyzed.Ministerio de Economía y CompetitividadElsevierEstadística e Investigación OperativaFQM331: Métodos y Modelos de la Estadística y la Investigación OperativaMinisterio de Economía y Competitividad (MINECO). España2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/submittedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/11441/61450https://doi.org/10.1016/j.ejor.2017.04.023reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésEuropean Journal of Operational Research, 262 (3), 863-878.info:eu-repo/grantAgreement/MINECO/MTM2016-74983-C2-1-R/info:eu-repo/grantAgreement/MINECO/MTM2015-63779-R/http://ac.els-cdn.com/S0377221717303569/1-s2.0-S0377221717303569-main.pdf?_tid=39e19780-571e-11e7-a8dc-00000aacb360&acdnat=1498117479_857be2b947ca88f8fc7938de9b973341info:eu-repo/semantics/openAccessoai:idus.us.es:11441/614502026-06-17T12:51:07Z
dc.title.none.fl_str_mv Minimum spanning trees with neighborhoods: mathematical programming formulations and solution methods
title Minimum spanning trees with neighborhoods: mathematical programming formulations and solution methods
spellingShingle Minimum spanning trees with neighborhoods: mathematical programming formulations and solution methods
Blanco Izquierdo, Víctor
Minimum spanning trees
Neighborhoods
Mixed integer non linear programming
Second order cone programming
title_short Minimum spanning trees with neighborhoods: mathematical programming formulations and solution methods
title_full Minimum spanning trees with neighborhoods: mathematical programming formulations and solution methods
title_fullStr Minimum spanning trees with neighborhoods: mathematical programming formulations and solution methods
title_full_unstemmed Minimum spanning trees with neighborhoods: mathematical programming formulations and solution methods
title_sort Minimum spanning trees with neighborhoods: mathematical programming formulations and solution methods
dc.creator.none.fl_str_mv Blanco Izquierdo, Víctor
Fernández Aréizaga, Elena
Puerto Albandoz, Justo
author Blanco Izquierdo, Víctor
author_facet Blanco Izquierdo, Víctor
Fernández Aréizaga, Elena
Puerto Albandoz, Justo
author_role author
author2 Fernández Aréizaga, Elena
Puerto Albandoz, Justo
author2_role author
author
dc.contributor.none.fl_str_mv Estadística e Investigación Operativa
FQM331: Métodos y Modelos de la Estadística y la Investigación Operativa
Ministerio de Economía y Competitividad (MINECO). España
dc.subject.none.fl_str_mv Minimum spanning trees
Neighborhoods
Mixed integer non linear programming
Second order cone programming
topic Minimum spanning trees
Neighborhoods
Mixed integer non linear programming
Second order cone programming
description This paper studies Minimum Spanning Trees under incomplete information for its vertices. We assume that no information is available on the precise placement of vertices so that it is only known that vertices belong to some neighborhoods that are second order cone representable and distances are measured with a ℓq-norm. Two mixed integer non linear mathematical programming formulations are presented, based on alternative representations of subtour elimination constraints. A solution scheme is also proposed, resulting from a reformulation suitable for a Benders-like decomposition, which is embedded within an exact branch-and-cut framework. Furthermore, a mathheuristic is developed, which alternates in solving convex subproblems in different solution spaces, and is able to solve larger instances. The results of extensive computational experiments are reported and analyzed.
publishDate 2017
dc.date.none.fl_str_mv 2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/submittedVersion
format article
status_str submittedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11441/61450
https://doi.org/10.1016/j.ejor.2017.04.023
url http://hdl.handle.net/11441/61450
https://doi.org/10.1016/j.ejor.2017.04.023
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv European Journal of Operational Research, 262 (3), 863-878.
info:eu-repo/grantAgreement/MINECO/MTM2016-74983-C2-1-R/
info:eu-repo/grantAgreement/MINECO/MTM2015-63779-R/
http://ac.els-cdn.com/S0377221717303569/1-s2.0-S0377221717303569-main.pdf?_tid=39e19780-571e-11e7-a8dc-00000aacb360&acdnat=1498117479_857be2b947ca88f8fc7938de9b973341
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 Elsevier
publisher.none.fl_str_mv Elsevier
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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