Initialization and Local Search Methods Applied to the Set Covering Problem: A Systematic Mapping

The set covering problem (SCP) is a classical combinatorial  optimization problem part of Karp's 21 NP-complete problems. Many real-world applications can be modeled as set covering problems (SCPs), such as locating emergency services, military planning, and decision-making in a COVID-19 pandem...

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Autores:
Tipo de recurso:
Fecha de publicación:
2023
Institución:
Universidad Pedagógica y Tecnológica de Colombia
Repositorio:
RiUPTC: Repositorio Institucional UPTC
Idioma:
eng
OAI Identifier:
oai:repositorio.uptc.edu.co:001/14364
Acceso en línea:
https://revistas.uptc.edu.co/index.php/ingenieria/article/view/15235
https://repositorio.uptc.edu.co/handle/001/14364
Palabra clave:
set covering problem
local search
systematic mapping
heuristics
initialization
metaheuristics
optimization
problema de cobertura de conjuntos
búsqueda local
mapeo sistemático
heurísticas
inicialización
metaheurísticas
optimización
Rights
License
http://creativecommons.org/licenses/by/4.0
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dc.title.en-US.fl_str_mv Initialization and Local Search Methods Applied to the Set Covering Problem: A Systematic Mapping
dc.title.es-ES.fl_str_mv Métodos de inicialización y búsqueda local aplicados al problema de cobertura de conjuntos: un mapeo sistemático
title Initialization and Local Search Methods Applied to the Set Covering Problem: A Systematic Mapping
spellingShingle Initialization and Local Search Methods Applied to the Set Covering Problem: A Systematic Mapping
set covering problem
local search
systematic mapping
heuristics
initialization
metaheuristics
optimization
problema de cobertura de conjuntos
búsqueda local
mapeo sistemático
heurísticas
inicialización
metaheurísticas
optimización
title_short Initialization and Local Search Methods Applied to the Set Covering Problem: A Systematic Mapping
title_full Initialization and Local Search Methods Applied to the Set Covering Problem: A Systematic Mapping
title_fullStr Initialization and Local Search Methods Applied to the Set Covering Problem: A Systematic Mapping
title_full_unstemmed Initialization and Local Search Methods Applied to the Set Covering Problem: A Systematic Mapping
title_sort Initialization and Local Search Methods Applied to the Set Covering Problem: A Systematic Mapping
dc.subject.en-US.fl_str_mv set covering problem
local search
systematic mapping
heuristics
initialization
metaheuristics
optimization
topic set covering problem
local search
systematic mapping
heuristics
initialization
metaheuristics
optimization
problema de cobertura de conjuntos
búsqueda local
mapeo sistemático
heurísticas
inicialización
metaheurísticas
optimización
dc.subject.es-ES.fl_str_mv problema de cobertura de conjuntos
búsqueda local
mapeo sistemático
heurísticas
inicialización
metaheurísticas
optimización
description The set covering problem (SCP) is a classical combinatorial  optimization problem part of Karp's 21 NP-complete problems. Many real-world applications can be modeled as set covering problems (SCPs), such as locating emergency services, military planning, and decision-making in a COVID-19 pandemic context. Among the approaches that this type of problem has solved are heuristic (H) and metaheuristic (MH) algorithms, which integrate iterative methods and procedures to explore and exploit the search space intelligently. In the present research, we carry out a systematic mapping of the literature focused on the initialization and local search methods used in these algorithms that have been applied to the SCP in order to identify them and that they can be applied in other algorithms. This mapping was carried out in three main stages: research planning, implementation, and documentation of results. The results indicate that the most used initialization method is random with heuristic search, and the inclusion of local search methods in MH algorithms improves the results obtained in comparison to those without local search. Moreover, initialization and local search methods can be used to modify other algorithms and evaluate the impact they generate on the results obtained.
publishDate 2023
dc.date.accessioned.none.fl_str_mv 2024-07-05T19:12:10Z
dc.date.available.none.fl_str_mv 2024-07-05T19:12:10Z
dc.date.none.fl_str_mv 2023-02-28
dc.type.none.fl_str_mv info:eu-repo/semantics/article
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.coarversion.spa.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a457
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistas.uptc.edu.co/index.php/ingenieria/article/view/15235
10.19053/01211129.v32.n63.2023.15235
dc.identifier.uri.none.fl_str_mv https://repositorio.uptc.edu.co/handle/001/14364
url https://revistas.uptc.edu.co/index.php/ingenieria/article/view/15235
https://repositorio.uptc.edu.co/handle/001/14364
identifier_str_mv 10.19053/01211129.v32.n63.2023.15235
dc.language.none.fl_str_mv eng
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistas.uptc.edu.co/index.php/ingenieria/article/view/15235/12691
https://revistas.uptc.edu.co/index.php/ingenieria/article/view/15235/13183
dc.rights.en-US.fl_str_mv http://creativecommons.org/licenses/by/4.0
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.coar.spa.fl_str_mv http://purl.org/coar/access_right/c_abf374
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0
http://purl.org/coar/access_right/c_abf374
http://purl.org/coar/access_right/c_abf2
dc.format.none.fl_str_mv application/pdf
text/xml
dc.publisher.en-US.fl_str_mv Universidad Pedagógica y Tecnológica de Colombia
dc.source.en-US.fl_str_mv Revista Facultad de Ingeniería; Vol. 32 No. 63 (2023): January-March 2023 (Continuous Publication); e15235
dc.source.es-ES.fl_str_mv Revista Facultad de Ingeniería; Vol. 32 Núm. 63 (2023): Enero-Marzo 2023 (Publicación Continua); e15235
dc.source.none.fl_str_mv 2357-5328
0121-1129
institution Universidad Pedagógica y Tecnológica de Colombia
repository.name.fl_str_mv Repositorio Institucional UPTC
repository.mail.fl_str_mv repositorio.uptc@uptc.edu.co
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spelling 2023-02-282024-07-05T19:12:10Z2024-07-05T19:12:10Zhttps://revistas.uptc.edu.co/index.php/ingenieria/article/view/1523510.19053/01211129.v32.n63.2023.15235https://repositorio.uptc.edu.co/handle/001/14364The set covering problem (SCP) is a classical combinatorial  optimization problem part of Karp's 21 NP-complete problems. Many real-world applications can be modeled as set covering problems (SCPs), such as locating emergency services, military planning, and decision-making in a COVID-19 pandemic context. Among the approaches that this type of problem has solved are heuristic (H) and metaheuristic (MH) algorithms, which integrate iterative methods and procedures to explore and exploit the search space intelligently. In the present research, we carry out a systematic mapping of the literature focused on the initialization and local search methods used in these algorithms that have been applied to the SCP in order to identify them and that they can be applied in other algorithms. This mapping was carried out in three main stages: research planning, implementation, and documentation of results. The results indicate that the most used initialization method is random with heuristic search, and the inclusion of local search methods in MH algorithms improves the results obtained in comparison to those without local search. Moreover, initialization and local search methods can be used to modify other algorithms and evaluate the impact they generate on the results obtained.El problema de cobertura de conjuntos (PCC) es un problema de optimización combinatorio clásico que hace parte de los 21 problemas NP-completos de Karp. Muchas aplicaciones del mundo real pueden modelarse como PCC, como la ubicación servicios de emergencia, la planificación militar, la toma de decisiones en el contexto de la pandemia por COVID-19, entre otros. Entre los enfoques que han resuelto este tipo de problema se encuentran los algoritmos heurísticos (H) y metaheurísticos (MH), que integran métodos y procedimientos iterativos para explorar y explotar el espacio de búsqueda de forma inteligente. En la presente investigación realizamos un mapeo sistemático de la literatura enfocado en los métodos de inicialización y búsqueda local utilizados en estos algoritmos que se han aplicado al PCC con el fin de identificarlos y que puedan ser aplicados en otros algoritmos. Este mapeo se realizó en tres etapas principales: planificación de la investigación, ejecución y documentación de resultados. Se encontró que el método de inicialización más utilizado es el aleatorio con búsqueda heurística y que la inclusión de métodos de búsqueda local en los algoritmos MH mejoran los resultados obtenidos en comparación con estos sin búsqueda local. Por otra parte, se identificaron métodos de inicialización y búsqueda local que pueden ser utilizados para modificar otros algoritmos y evaluar el impacto que generan en los resultados obtenidos.application/pdftext/xmlengengUniversidad Pedagógica y Tecnológica de Colombiahttps://revistas.uptc.edu.co/index.php/ingenieria/article/view/15235/12691https://revistas.uptc.edu.co/index.php/ingenieria/article/view/15235/13183Copyright (c) 2023 Nelson-Enrique Quemá-Taimbud, Martha-Eliana Mendoza-Becerra, Oscar-Fernando Bedoya-Leyvahttp://creativecommons.org/licenses/by/4.0http://purl.org/coar/access_right/c_abf374http://purl.org/coar/access_right/c_abf2Revista Facultad de Ingeniería; Vol. 32 No. 63 (2023): January-March 2023 (Continuous Publication); e15235Revista Facultad de Ingeniería; Vol. 32 Núm. 63 (2023): Enero-Marzo 2023 (Publicación Continua); e152352357-53280121-1129set covering problemlocal searchsystematic mappingheuristicsinitializationmetaheuristicsoptimizationproblema de cobertura de conjuntosbúsqueda localmapeo sistemáticoheurísticasinicializaciónmetaheurísticasoptimizaciónInitialization and Local Search Methods Applied to the Set Covering Problem: A Systematic MappingMétodos de inicialización y búsqueda local aplicados al problema de cobertura de conjuntos: un mapeo sistemáticoinfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a457http://purl.org/coar/version/c_970fb48d4fbd8a85Quemá-Taimbud, Nelson-EnriqueMendoza-Becerra, Martha-ElianaBedoya-Leyva, Oscar-Fernando001/14364oai:repositorio.uptc.edu.co:001/143642025-07-18 11:53:51.374metadata.onlyhttps://repositorio.uptc.edu.coRepositorio Institucional UPTCrepositorio.uptc@uptc.edu.co