Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81215
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dc.contributorDepartment of Building and Real Estate-
dc.creatorTao, X-
dc.creatorLi, H-
dc.creatorMao, C-
dc.creatorWang, C-
dc.creatorHui Yap, JB-
dc.creatorSepasgozar, S-
dc.creatorShirowzhan S-
dc.creatorRose T-
dc.date.accessioned2019-08-23T08:29:47Z-
dc.date.available2019-08-23T08:29:47Z-
dc.identifier.issn1687-8086en_US
dc.identifier.urihttp://hdl.handle.net/10397/81215-
dc.language.isoenen_US
dc.publisherHindawi Publishing Corporationen_US
dc.rightsCopyright © 2019 Xingyu Tao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.rightsThe following publication Xingyu Tao, Heng Li, Chao Mao, et al., “Developing Shuffled Frog-Leaping Algorithm (SFLA) Method to Solve Power Load-Constrained TCRTO Problems in Civil Engineering,” Advances in Civil Engineering, vol. 2019, Article ID 1404636, 16 pages, 2019 is available at https://doi.org/10.1155/2019/1404636en_US
dc.titleDeveloping Shuffled Frog-Leaping Algorithm (SFLA) method to solve power load-constrained TCRTO problems in civil engineeringen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume2019en_US
dc.identifier.doi10.1155/2019/1404636en_US
dcterms.abstractIt is extensively acknowledged that excessive on-site electricity power load often causes power failure across a construction site and surrounding residential zones and can result in unforeseen schedule delay, construction quality problems, life inconvenience, and even property loss. However, energy management, such as power load optimization, has long been ignored in construction scheduling. This study aims to develop a modified shuffled frog-leaping algorithm (SFLA) approach in project scheduling to aid decision-makers in identifying the best Pareto solution for time-cost-resource trade-off (TCRTO) problems under the constraint of precedence, resource availability, and on-site peak electricity power load. A mathematical model including three objective functions and five constraints was established followed by the application of the modified SLFA on real-case multiobjective optimization problems in construction scheduling. The performance of SLFA was compared with that of the nondominated sorting genetic algorithm (NSGA II). The results showed that the developed new approach was superior in identifying optimal project planning solutions, which could essentially assist on-site power load-oriented schedule decision-making for construction teams.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAdvances in civil engineering, 2019, v. 2019, 1404636-
dcterms.isPartOfAdvances in civil engineering-
dcterms.issued2019-
dc.identifier.isiWOS:000473366000001-
dc.identifier.scopus2-s2.0-85066049181-
dc.identifier.eissn1687-8094en_US
dc.identifier.artn1404636en_US
dc.description.validate201908 bcma-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
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