A computational comparison of compact MILP formulations for the zero forcing number

Detalhes bibliográficos
Autor(a) principal: Agra, Agostinho
Data de Publicação: 2019
Outros Autores: Cerdeira, Jorge Orestes, Requejo, Cristina
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10773/27228
Resumo: Consider a graph where some of its vertices are colored. A colored vertex with a single uncolored neighbor forces that neighbor to become colored. A zero forcing set is a set of colored vertices that forces all vertices to become colored. The zero forcing number is the size of a minimum forcing set. Finding the minimum forcing set of a graph is NP-hard. We give a new compact mixed integer linear programming formulation (MILP) for this problem, and analyse this formulation and establish relation to an existing compact formulation and to two variants. In order to solve large size instances we propose a sequential search algorithm which can also be used as a heuristic to derive upper bounds for the zero forcing number. A computational study using Xpress (a MILP solver) is conducted to test the performances of the discussed compact formulations and the sequential search algorithm. We report results on cubic, Watts-Strogatz and randomly generated graphs with 10, 20 and 30 vertices.
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spelling A computational comparison of compact MILP formulations for the zero forcing numberGraphsMixed integer linear programmingCompact formulationsValid inequalitiesZero forcingConsider a graph where some of its vertices are colored. A colored vertex with a single uncolored neighbor forces that neighbor to become colored. A zero forcing set is a set of colored vertices that forces all vertices to become colored. The zero forcing number is the size of a minimum forcing set. Finding the minimum forcing set of a graph is NP-hard. We give a new compact mixed integer linear programming formulation (MILP) for this problem, and analyse this formulation and establish relation to an existing compact formulation and to two variants. In order to solve large size instances we propose a sequential search algorithm which can also be used as a heuristic to derive upper bounds for the zero forcing number. A computational study using Xpress (a MILP solver) is conducted to test the performances of the discussed compact formulations and the sequential search algorithm. We report results on cubic, Watts-Strogatz and randomly generated graphs with 10, 20 and 30 vertices.Elsevier2020-09-30T00:00:00Z2019-09-30T00:00:00Z2019-09-30info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/27228eng0166-218X10.1016/j.dam.2019.03.027Agra, AgostinhoCerdeira, Jorge OrestesRequejo, Cristinainfo: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:RCAAP2024-05-06T04:22:59Zoai:ria.ua.pt:10773/27228Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T14:06:36.090902Repositórios 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 computational comparison of compact MILP formulations for the zero forcing number
title A computational comparison of compact MILP formulations for the zero forcing number
spellingShingle A computational comparison of compact MILP formulations for the zero forcing number
Agra, Agostinho
Graphs
Mixed integer linear programming
Compact formulations
Valid inequalities
Zero forcing
title_short A computational comparison of compact MILP formulations for the zero forcing number
title_full A computational comparison of compact MILP formulations for the zero forcing number
title_fullStr A computational comparison of compact MILP formulations for the zero forcing number
title_full_unstemmed A computational comparison of compact MILP formulations for the zero forcing number
title_sort A computational comparison of compact MILP formulations for the zero forcing number
author Agra, Agostinho
author_facet Agra, Agostinho
Cerdeira, Jorge Orestes
Requejo, Cristina
author_role author
author2 Cerdeira, Jorge Orestes
Requejo, Cristina
author2_role author
author
dc.contributor.author.fl_str_mv Agra, Agostinho
Cerdeira, Jorge Orestes
Requejo, Cristina
dc.subject.por.fl_str_mv Graphs
Mixed integer linear programming
Compact formulations
Valid inequalities
Zero forcing
topic Graphs
Mixed integer linear programming
Compact formulations
Valid inequalities
Zero forcing
description Consider a graph where some of its vertices are colored. A colored vertex with a single uncolored neighbor forces that neighbor to become colored. A zero forcing set is a set of colored vertices that forces all vertices to become colored. The zero forcing number is the size of a minimum forcing set. Finding the minimum forcing set of a graph is NP-hard. We give a new compact mixed integer linear programming formulation (MILP) for this problem, and analyse this formulation and establish relation to an existing compact formulation and to two variants. In order to solve large size instances we propose a sequential search algorithm which can also be used as a heuristic to derive upper bounds for the zero forcing number. A computational study using Xpress (a MILP solver) is conducted to test the performances of the discussed compact formulations and the sequential search algorithm. We report results on cubic, Watts-Strogatz and randomly generated graphs with 10, 20 and 30 vertices.
publishDate 2019
dc.date.none.fl_str_mv 2019-09-30T00:00:00Z
2019-09-30
2020-09-30T00:00:00Z
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 http://hdl.handle.net/10773/27228
url http://hdl.handle.net/10773/27228
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0166-218X
10.1016/j.dam.2019.03.027
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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
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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
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