An Improved Greedy Heuristic for the Minimum Positive Influence Dominating Set Problem in Social Networks

This paper presents a performance comparison of greedy heuristics for a recent variant of the dominating set problem known as the minimum positive influence dominating set (MPIDS) problem. This APX-hard combinatorial optimization problem has applications in social networks. Its aim is to identify a...

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Detalhes bibliográficos
Autores: Bouamama, Salim, Blum, Christian
Formato: artículo
Fecha de publicación:2021
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/253028
Acesso em linha:http://hdl.handle.net/10261/253028
Access Level:acceso abierto
Palavra-chave:Greedy algorithm
Minimum positive influence dominating
Set problem
Heuristic search
Social networks
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spelling An Improved Greedy Heuristic for the Minimum Positive Influence Dominating Set Problem in Social NetworksBouamama, SalimBlum, ChristianGreedy algorithmMinimum positive influence dominatingSet problemHeuristic searchSocial networksThis paper presents a performance comparison of greedy heuristics for a recent variant of the dominating set problem known as the minimum positive influence dominating set (MPIDS) problem. This APX-hard combinatorial optimization problem has applications in social networks. Its aim is to identify a small subset of key influential individuals in order to facilitate the spread of positive influence in the whole network. In this paper, we focus on the development of a fast and effective greedy heuristic for the MPIDS problem, because greedy heuristics are an essential component of more sophisticated metaheuristics. Thus, the development of well-working greedy heuristics supports the development of efficient metaheuristics. Extensive experiments conducted on a wide range of social networks and complex networks confirm the overall superiority of our greedy algorithm over its competitors, especially when the problem size becomes large. Moreover, we compare our algorithm with the integer linear programming solver CPLEX. While the performance of CPLEX is very strong for small and medium-sized networks, it reaches its limits when being applied to the largest networks. However, even in the context of small and medium-sized networks, our greedy algorithm is only 2.53% worse than CPLEX.Multidisciplinary Digital Publishing InstituteConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2021202120212021info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501http://hdl.handle.net/10261/253028reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttp://dx.doi.org/10.3390/a14030079Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2530282026-05-22T06:33:51Z
dc.title.none.fl_str_mv An Improved Greedy Heuristic for the Minimum Positive Influence Dominating Set Problem in Social Networks
title An Improved Greedy Heuristic for the Minimum Positive Influence Dominating Set Problem in Social Networks
spellingShingle An Improved Greedy Heuristic for the Minimum Positive Influence Dominating Set Problem in Social Networks
Bouamama, Salim
Greedy algorithm
Minimum positive influence dominating
Set problem
Heuristic search
Social networks
title_short An Improved Greedy Heuristic for the Minimum Positive Influence Dominating Set Problem in Social Networks
title_full An Improved Greedy Heuristic for the Minimum Positive Influence Dominating Set Problem in Social Networks
title_fullStr An Improved Greedy Heuristic for the Minimum Positive Influence Dominating Set Problem in Social Networks
title_full_unstemmed An Improved Greedy Heuristic for the Minimum Positive Influence Dominating Set Problem in Social Networks
title_sort An Improved Greedy Heuristic for the Minimum Positive Influence Dominating Set Problem in Social Networks
dc.creator.none.fl_str_mv Bouamama, Salim
Blum, Christian
author Bouamama, Salim
author_facet Bouamama, Salim
Blum, Christian
author_role author
author2 Blum, Christian
author2_role author
dc.contributor.none.fl_str_mv Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Greedy algorithm
Minimum positive influence dominating
Set problem
Heuristic search
Social networks
topic Greedy algorithm
Minimum positive influence dominating
Set problem
Heuristic search
Social networks
description This paper presents a performance comparison of greedy heuristics for a recent variant of the dominating set problem known as the minimum positive influence dominating set (MPIDS) problem. This APX-hard combinatorial optimization problem has applications in social networks. Its aim is to identify a small subset of key influential individuals in order to facilitate the spread of positive influence in the whole network. In this paper, we focus on the development of a fast and effective greedy heuristic for the MPIDS problem, because greedy heuristics are an essential component of more sophisticated metaheuristics. Thus, the development of well-working greedy heuristics supports the development of efficient metaheuristics. Extensive experiments conducted on a wide range of social networks and complex networks confirm the overall superiority of our greedy algorithm over its competitors, especially when the problem size becomes large. Moreover, we compare our algorithm with the integer linear programming solver CPLEX. While the performance of CPLEX is very strong for small and medium-sized networks, it reaches its limits when being applied to the largest networks. However, even in the context of small and medium-sized networks, our greedy algorithm is only 2.53% worse than CPLEX.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/253028
url http://hdl.handle.net/10261/253028
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv http://dx.doi.org/10.3390/a14030079
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869402691775496192
score 15,812455

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