Integrating a novel multiple-objective FBI with BIM to determine tradeoff among resources in project scheduling

被引:25
作者
Dang-Trinh Nguyen [1 ,2 ]
Jui-Sheng Chou [3 ]
Duc-Hoc Tran [1 ,2 ]
机构
[1] Ho Chi Minh City Univ Technol HCMUT, Fac Civil Engn, 268 Ly Thuong Kiet St,Dist 10, Ho Chi Minh City, Vietnam
[2] Vietnam Natl Univ Ho Chi Minh City, Ho Chi Minh City, Vietnam
[3] Natl Taiwan Univ Sci & Technol, Dept Civil & Construct Engn, 43,Sec 4,Keelung Rd, Taipei, Taiwan
关键词
Resource management; Project resource management; Building information modeling; Forensic-based investigation; Multi-criteria decision-making; PARTICLE SWARM OPTIMIZATION; ARTIFICIAL BEE COLONY; MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS; COST-QUALITY TRADEOFF; CONSTRUCTION PROJECTS; DISCRETE-TIME; DIFFERENTIAL EVOLUTION; OFF PROBLEMS; PERFORMANCE; MANAGEMENT;
D O I
10.1016/j.knosys.2021.107640
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Project managers face a challenge when they must trade-off various resource factors such as time, cost, quality, safety, and the environment. Such challenges increase with the size and complexity of the project. This investigation develops a framework for making tradeoffs among resources in project scheduling that fuses building information modeling (BIM), multi-objective optimization (MOO), and multi-criteria decision-making (MCDM). First, a 3D model is constructed using BIM construction management software. This model generates a bill of quantities to specify required project resources. Then, a novel multiple-objective forensic-based investigation (MOFBI) is introduced to provide the optimal solution set. Finally, a generic evidence-based multi-criteria decision analysis method is used to determine the best schedule for project execution. Three project scheduling problems are presented to demonstrate the efficiency and effectiveness of the proposed framework. The obtained results reveal that MOFBI can find outcome curves with a high uniform distribution of solutions and visual analytics. (C) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页数:16
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