A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem

Autores
Amandi, Analia Adriana; Yannibelli, Virginia Daniela
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this paper, we address a project scheduling problem. This problem considers a priority optimization objective for project managers. This objective implies assigning the most effective set of human resources to each project activity. To solve the problem, we propose a hybrid evolutionary algorithm. This algorithm incorporates a diversity-adaptive simulated annealing algorithm into the framework of an evolutionary algorithm with the aim of improving the performance of the evolutionary search. The simulated annealing algorithm adapts its behavior according to the fluctuation of diversity of evolutionary algorithm population. The performance of the hybrid evolutionary algorithm on six different instance sets is compared with those of the algorithms previously proposed in the literature for solving the addressed problem. The obtained results show that the hybrid evolutionary algorithm significantly outperforms the previous algorithms.
Fil: Amandi, Analia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Yannibelli, Virginia Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Materia
Project Scheduling
Human Resource Assignment
Multi-Skilled Resources
Hybrid Evolutionary Algorithms
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/6798
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/6798
network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling ProblemAmandi, Analia AdrianaYannibelli, Virginia DanielaProject SchedulingHuman Resource AssignmentMulti-Skilled ResourcesHybrid Evolutionary Algorithmshttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1In this paper, we address a project scheduling problem. This problem considers a priority optimization objective for project managers. This objective implies assigning the most effective set of human resources to each project activity. To solve the problem, we propose a hybrid evolutionary algorithm. This algorithm incorporates a diversity-adaptive simulated annealing algorithm into the framework of an evolutionary algorithm with the aim of improving the performance of the evolutionary search. The simulated annealing algorithm adapts its behavior according to the fluctuation of diversity of evolutionary algorithm population. The performance of the hybrid evolutionary algorithm on six different instance sets is compared with those of the algorithms previously proposed in the literature for solving the addressed problem. The obtained results show that the hybrid evolutionary algorithm significantly outperforms the previous algorithms.Fil: Amandi, Analia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Yannibelli, Virginia Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaSpringer2014-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/6798Amandi, Analia Adriana; Yannibelli, Virginia Daniela; A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem; Springer; Lecture Notes In Computer Science; 8669; 9-2014; 412-4230302-9743enginfo:eu-repo/semantics/altIdentifier/url/http://link.springer.com/chapter/10.1007%2F978-3-319-10840-7_50info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-319-10840-7_50info:eu-repo/semantics/altIdentifier/doi/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:40:56Zoai:ri.conicet.gov.ar:11336/6798instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:40:56.958CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem
title A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem
spellingShingle A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem
Amandi, Analia Adriana
Project Scheduling
Human Resource Assignment
Multi-Skilled Resources
Hybrid Evolutionary Algorithms
title_short A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem
title_full A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem
title_fullStr A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem
title_full_unstemmed A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem
title_sort A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem
dc.creator.none.fl_str_mv Amandi, Analia Adriana
Yannibelli, Virginia Daniela
author Amandi, Analia Adriana
author_facet Amandi, Analia Adriana
Yannibelli, Virginia Daniela
author_role author
author2 Yannibelli, Virginia Daniela
author2_role author
dc.subject.none.fl_str_mv Project Scheduling
Human Resource Assignment
Multi-Skilled Resources
Hybrid Evolutionary Algorithms
topic Project Scheduling
Human Resource Assignment
Multi-Skilled Resources
Hybrid Evolutionary Algorithms
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In this paper, we address a project scheduling problem. This problem considers a priority optimization objective for project managers. This objective implies assigning the most effective set of human resources to each project activity. To solve the problem, we propose a hybrid evolutionary algorithm. This algorithm incorporates a diversity-adaptive simulated annealing algorithm into the framework of an evolutionary algorithm with the aim of improving the performance of the evolutionary search. The simulated annealing algorithm adapts its behavior according to the fluctuation of diversity of evolutionary algorithm population. The performance of the hybrid evolutionary algorithm on six different instance sets is compared with those of the algorithms previously proposed in the literature for solving the addressed problem. The obtained results show that the hybrid evolutionary algorithm significantly outperforms the previous algorithms.
Fil: Amandi, Analia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Yannibelli, Virginia Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
description In this paper, we address a project scheduling problem. This problem considers a priority optimization objective for project managers. This objective implies assigning the most effective set of human resources to each project activity. To solve the problem, we propose a hybrid evolutionary algorithm. This algorithm incorporates a diversity-adaptive simulated annealing algorithm into the framework of an evolutionary algorithm with the aim of improving the performance of the evolutionary search. The simulated annealing algorithm adapts its behavior according to the fluctuation of diversity of evolutionary algorithm population. The performance of the hybrid evolutionary algorithm on six different instance sets is compared with those of the algorithms previously proposed in the literature for solving the addressed problem. The obtained results show that the hybrid evolutionary algorithm significantly outperforms the previous algorithms.
publishDate 2014
dc.date.none.fl_str_mv 2014-09
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/6798
Amandi, Analia Adriana; Yannibelli, Virginia Daniela; A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem; Springer; Lecture Notes In Computer Science; 8669; 9-2014; 412-423
0302-9743
url http://hdl.handle.net/11336/6798
identifier_str_mv Amandi, Analia Adriana; Yannibelli, Virginia Daniela; A Diversity-Adaptive Hybrid Evolutionary Algorithm to Solve a Project Scheduling Problem; Springer; Lecture Notes In Computer Science; 8669; 9-2014; 412-423
0302-9743
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://link.springer.com/chapter/10.1007%2F978-3-319-10840-7_50
info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-319-10840-7_50
info:eu-repo/semantics/altIdentifier/doi/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
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:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.069144

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