An applied grey wolf optimizer for scheduling construction projects
Email:
trangtt_ph@utc.edu.vn
Từ khóa:
project delay, project scheduling, cost overrun, Grey Wolf Optimizer, construction management, project performance.
Tóm tắt
Construction project delay has been reported as a significant cause of the project’s failure, which results in cost overrun, thereby decreasing the effectiveness of the project. Therefore, project management has placed much effort in construction works’ scheduling to enhance project performance. However, construction schedule has been commonly addressed within traditional methods that rely on project managers’ subjective experiences and manually-performed approaches, resulting in time-consuming and inaccurate decision-making. This study is thus aimed to handle these limitations. Using analyses of the Grey Wolf Optimizer (GWO) model, inspired by the leadership hierarchy and hunting mechanism of grey wolves in nature, this study supports reducing the construction time and minimizing the additional construction cost. Furthermore, another computational tool, namely Solver-addins, is also used to verify the reliability of the result. The findings of this study will provide a valuable tool for supporting construction management to deliver projects on time, improving construction project performanceTài liệu tham khảo
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[2]. M. Tian, R. J. Liu, G. J. Zhang, Solving the resource-constrained multi-project scheduling problem with an improved critical chain method, Journal of the Operational Research Society, 71 (2020) 1243–1258. https://doi.org/10.1080/01605682.2019.1609883
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[4]. M. Zhao, X. Wang, J. Yu, L. Bi, Y. Xiao, J. Zhang, Optimization of Construction Duration and Schedule Robustness Based on Hybrid Grey Wolf Optimizer with Sine Cosine Algorithm, Energies, 215 (2020). https://doi.org/10.3390/en13010215
[5]. P. Shahsavand, A. Marefat, M. Parchamijalal, Causes of delays in construction industry and comparative delay analysis techniques with SCL protocol, ECAM, 25 (2018) 497–533. https://doi.org/10.1108/ECAM-10-2016-0220
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[7]. L. Ho Viet, T. Trinh Thi, B. Ho Xuan, Swarm intelligence-based technique to enhance performance of ANN in structural damage detection, Transport and communications science Journal, 1 (2022) 1–15. https://doi.org/10.47869/tcsj.73.1.1
[8]. E. K. Burke, G. Kendall (eds), Search Methodologies, Springer, Boston, MA, (2005) 401-435. https://doi.org/10.1007/0-387-28356-0_14
[9]. H. John Holland, Genetic Algorithms, Scientific American, 267 (1992) 66–73 (Accessed 4 Aug. 2021).
[10]. S. Kirkpatrick, C. D. Gelatt, Jr., M. P. Vecchi, Optimization by Simulated Annealing, 220 (1983) 671-680. https://doi.org/10.1126/science.220.4598.671
[11]. E. Rashedi, H. Nezamabadi-pour, S. Saryazdi, A Gravitational Search Algorithm, Information Sciences, 179 (2009) 2232–2248. https://doi.org/10.1016/j.ins.2009.03.004
[12]. X. S. Yang, Firefly algorithm: stochastic test functions and design optimization, IJBIC, 78 (2010). https://doi.org/10.1504/IJBIC.2010.032124
[13]. X.-S. Yang, D. A. Pelta, C. Cruz, G. Terrazas, N. Krasnogor, J. R. González, A New Metaheuristic Bat-Inspired Algorithm in Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), Springer Berlin Heidelberg, 284 (2010) 65–74. https://doi.org/10.1007/978-3-642-12538-6_6
[14]. S. Mirjalili, A. Lewis, Grey Wolf Optimizer, Advances in Engineering Software, 69 (2014) 46–61. https://doi.org/10.1016/j.advengsoft.2013.12.007
[15]. H. Faris, I. Aljarah, M. A. Al-Betar, S. Mirjalili, Grey wolf optimizer: a review of recent variants and applications, Neural Comput & Applic, 30 (2018) 413–435. https://doi.org/10.1007/s00521-017-3272-5
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[22]. C. T. Hoang, T. H. Nguyen, H. T. Phung, Network diagram optimization under standard of time and cost by using Genetic Algorithms, Journal of Science and Technology, 122 (2014) 47-52.
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Nhận bài
05/08/2021
Nhận bài sửa
21/12/2021
Chấp nhận đăng
25/02/2022
Xuất bản
15/05/2022
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Kiểu trích dẫn
Trinh Thi, T., & Nguyen Luong, H. (7600). An applied grey wolf optimizer for scheduling construction projects . Tạp Chí Khoa Học Giao Thông Vận Tải, 73(4), 397-411. https://doi.org/10.47869/tcsj.73.4.5
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