Hybrid Genetic Algorithm with Simulated Annealing for Resource-Constrained Project Scheduling

Basit Öğe Kaydı
dc.authoridBettemir, Önder/0000-0002-5692-7708
dc.authoridSonmez, Rifat/0000-0001-6163-3264
dc.authorwosidBettemir, Önder/ABG-8533-2020
dc.authorwosidSonmez, Rifat/AAQ-4963-2020
dc.contributor.authorBettemir, Onder Halis
dc.contributor.authorSonmez, Rifat
dc.date.accessioned2024-08-04T20:41:08Z
dc.date.available2024-08-04T20:41:08Z
dc.date.issued2015
dc.departmentİnönü Üniversitesien_US
dc.description.abstractResource-constrained project scheduling problem (RCPSP) is a very important optimization problem in construction project management. Despite the importance of the RCPSP in project scheduling and management, commercial project management software provides very limited capabilities for the RCPSP. In this paper, a hybrid strategy based on genetic algorithms, and simulated annealing is presented for the RCPSP. The strategy aims to integrate parallel search ability of genetic algorithms with fine tuning capabilities of the simulated annealing technique to achieve an efficient algorithm for the RCPSP. The proposed strategy was tested using benchmark test problems and best solutions of the state-of-the-art algorithms. A sole genetic algorithm, and seven heuristics of project management software were also included in the computational experiments. Computational results show that the proposed hybrid strategy improves convergence of sole genetic algorithm and provides a competitive alternative for the RCPSP. The computational experiments also reveal the limitations of the project management software for resource-constrained project scheduling. (C) 2014 American Society of Civil Engineers.en_US
dc.identifier.doi10.1061/(ASCE)ME.1943-5479.0000323
dc.identifier.issn0742-597X
dc.identifier.issn1943-5479
dc.identifier.issue5en_US
dc.identifier.scopus2-s2.0-84939475842en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1061/(ASCE)ME.1943-5479.0000323
dc.identifier.urihttps://hdl.handle.net/11616/96932
dc.identifier.volume31en_US
dc.identifier.wosWOS:000359939100016en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherAsce-Amer Soc Civil Engineersen_US
dc.relation.ispartofJournal of Management in Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectResource-constrained project schedulingen_US
dc.subjectGenetic algorithmsen_US
dc.subjectSimulated annealingen_US
dc.subjectHybrid algorithmsen_US
dc.subjectProject management softwareen_US
dc.titleHybrid Genetic Algorithm with Simulated Annealing for Resource-Constrained Project Schedulingen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu