Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach

Purpose: The issue resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resource over-allocating drawback is frequently seen after scheduling of a project in practice which causes a schedule to be useless. Modifying an over-allocated schedu...

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Detalhes bibliográficos
Autores: Delgoshaei, Aidin, Ariffin, Mohd Khairol Mohd, Baharudin, B.T. H.T.
Formato: artículo
Fecha de publicación:2016
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/91376
Acesso em linha:https://hdl.handle.net/2117/91376
https://dx.doi.org/10.3926/jiem.1522
Access Level:acceso abierto
Palavra-chave:Project management--Planning
Multimode project scheduling
Genetic algorithm
Pre-emptive resource-constrained
Discounted cash flows
Gestió de projectes -- Planificació
Àrees temàtiques de la UPC::Economia i organització d'empreses::Direcció d'operacions
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spelling Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approachDelgoshaei, AidinAriffin, Mohd Khairol MohdBaharudin, B.T. H.T.Project management--PlanningMultimode project schedulingGenetic algorithmPre-emptive resource-constrainedDiscounted cash flowsGestió de projectes -- PlanificacióÀrees temàtiques de la UPC::Economia i organització d'empreses::Direcció d'operacionsPurpose: The issue resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resource over-allocating drawback is frequently seen after scheduling of a project in practice which causes a schedule to be useless. Modifying an over-allocated schedule is very complicated and needs a lot of efforts and time. In this paper, a new and fast tracking method is proposed to schedule large scale projects which can help project engineers to schedule the project rapidly and with more confidence. Design/methodology/approach: In this article, a forward approach for maximizing net present value (NPV) in multi-mode resource constrained project scheduling problem while assuming discounted positive cash flows (MRCPSP-DCF) is proposed. The progress payment method is used and all resources are considered as pre-emptible. The proposed approach maximizes NPV using unscheduled resources through resource calendar in forward mode. For this purpose, a Genetic Algorithm is applied to solve. Findings: The findings show that the proposed method is an effective way to maximize NPV in MRCPSP-DCF problems while activity splitting is allowed. The proposed algorithm is very fast and can schedule experimental cases with 1000 variables and 100 resources in few seconds. The results are then compared with branch and bound method and simulated annealing algorithm and it is found the proposed genetic algorithm can provide results with better quality. Then algorithm is then applied for scheduling a hospital in practice. Originality/value: The method can be used alone or as a macro in Microsoft Office Project® Software to schedule MRCPSP-DCF problems or to modify resource over-allocated activities after scheduling a project. This can help project engineers to schedule project activities rapidly with more accuracy in practice.Peer ReviewedOmniaScience20162016-10-0120162016-11-02journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/91376https://dx.doi.org/10.3926/jiem.1522reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial 3.0 Spainhttp://creativecommons.org/licenses/by-nc/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/913762026-05-27T15:37:01Z
dc.title.none.fl_str_mv Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach
title Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach
spellingShingle Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach
Delgoshaei, Aidin
Project management--Planning
Multimode project scheduling
Genetic algorithm
Pre-emptive resource-constrained
Discounted cash flows
Gestió de projectes -- Planificació
Àrees temàtiques de la UPC::Economia i organització d'empreses::Direcció d'operacions
title_short Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach
title_full Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach
title_fullStr Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach
title_full_unstemmed Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach
title_sort Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach
dc.creator.none.fl_str_mv Delgoshaei, Aidin
Ariffin, Mohd Khairol Mohd
Baharudin, B.T. H.T.
author Delgoshaei, Aidin
author_facet Delgoshaei, Aidin
Ariffin, Mohd Khairol Mohd
Baharudin, B.T. H.T.
author_role author
author2 Ariffin, Mohd Khairol Mohd
Baharudin, B.T. H.T.
author2_role author
author
dc.subject.none.fl_str_mv Project management--Planning
Multimode project scheduling
Genetic algorithm
Pre-emptive resource-constrained
Discounted cash flows
Gestió de projectes -- Planificació
Àrees temàtiques de la UPC::Economia i organització d'empreses::Direcció d'operacions
topic Project management--Planning
Multimode project scheduling
Genetic algorithm
Pre-emptive resource-constrained
Discounted cash flows
Gestió de projectes -- Planificació
Àrees temàtiques de la UPC::Economia i organització d'empreses::Direcció d'operacions
description Purpose: The issue resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resource over-allocating drawback is frequently seen after scheduling of a project in practice which causes a schedule to be useless. Modifying an over-allocated schedule is very complicated and needs a lot of efforts and time. In this paper, a new and fast tracking method is proposed to schedule large scale projects which can help project engineers to schedule the project rapidly and with more confidence. Design/methodology/approach: In this article, a forward approach for maximizing net present value (NPV) in multi-mode resource constrained project scheduling problem while assuming discounted positive cash flows (MRCPSP-DCF) is proposed. The progress payment method is used and all resources are considered as pre-emptible. The proposed approach maximizes NPV using unscheduled resources through resource calendar in forward mode. For this purpose, a Genetic Algorithm is applied to solve. Findings: The findings show that the proposed method is an effective way to maximize NPV in MRCPSP-DCF problems while activity splitting is allowed. The proposed algorithm is very fast and can schedule experimental cases with 1000 variables and 100 resources in few seconds. The results are then compared with branch and bound method and simulated annealing algorithm and it is found the proposed genetic algorithm can provide results with better quality. Then algorithm is then applied for scheduling a hospital in practice. Originality/value: The method can be used alone or as a macro in Microsoft Office Project® Software to schedule MRCPSP-DCF problems or to modify resource over-allocated activities after scheduling a project. This can help project engineers to schedule project activities rapidly with more accuracy in practice.
publishDate 2016
dc.date.none.fl_str_mv 2016
2016-10-01
2016
2016-11-02
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/91376
https://dx.doi.org/10.3926/jiem.1522
url https://hdl.handle.net/2117/91376
https://dx.doi.org/10.3926/jiem.1522
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial 3.0 Spain
http://creativecommons.org/licenses/by-nc/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial 3.0 Spain
http://creativecommons.org/licenses/by-nc/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv OmniaScience
publisher.none.fl_str_mv OmniaScience
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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