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Arabi, S, Eshtehardian, E and Shafiei, I (2022) Using Bayesian Networks for Selecting Risk-Response Strategies in Construction Projects. Journal of Construction Engineering and Management, 148(08).
Chang, T, Chi, S and Im, S (2022) Understanding User Experience and Satisfaction with Urban Infrastructure through Text Mining of Civil Complaint Data. Journal of Construction Engineering and Management, 148(08).
Dias Barkokebas, R, Al-Hussein, M and Li, X (2022) VR–MOCAP-Enabled Ergonomic Risk Assessment of Workstation Prototypes in Offsite Construction. Journal of Construction Engineering and Management, 148(08).
Ezzeddine, A, Shehab, L, Lucko, G and Hamzeh, F (2022) Forecasting Construction Project Performance with Momentum Using Singularity Functions in LPS. Journal of Construction Engineering and Management, 148(08).
Feng, K, Wang, S, Lu, W, Liu, C and Wang, Y (2022) Planning Construction Projects in Deep Uncertainty: A Data-Driven Uncertainty Analysis Approach. Journal of Construction Engineering and Management, 148(08).
- Type: Journal Article
- Keywords: Construction planning; Deep uncertainty; Decision making; Robustness; Vulnerability analysis;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0002315
- Abstract:
Construction planning is significantly affected by many uncertain factors derived from construction tasks, the environments, resources, technologies, personnel, and more. Uncertainty analysis approaches are thus critical to supporting the decision making associated with construction planning. However, the precise probability distributions (PDs) of uncertain factors are sometimes inaccessible, especially for construction projects in a novel context with limited previous experiences or similar references. These situations constitute a deep uncertainty problem, and probability-based methods are no longer applicable for construction planning. To address this challenge, an uncertainty analysis approach that integrates Latin hypercube sampling (LHS), discrete-event simulation (DES), and the patient rule induction method (PRIM) is proposed. Specifically, it is progressed by LHS and DES to generate a wide array of uncertainty scenarios represented by possible PDs to quantify the robustness of various construction decisions; then, PRIM is used to identify the vulnerable scenarios that will jeopardize project completion. The approach was implemented on a real-world project, and the results demonstrated that it was able to identify the most robust construction schemes and vulnerable scenarios for construction planning. This research contributes a data-driven technology that provides an uncertainty analysis approach for construction planning without relying on assumed probability distributions from limited, unreliable project references.
Gomes Araújo, L and Lucko, G (2022) Best Practices for Case Studies in Construction Engineering and Management Research. Journal of Construction Engineering and Management, 148(08).
Heaton, R, Martin, H, Chadee, A, Milling, A, Dunne, S and Borthwick, F (2022) The Construction Materials Conundrum: Practical Solutions to Address Integrated Supply Chain Complexities. Journal of Construction Engineering and Management, 148(08).
Islam, M S, Mohandes, S R, Mahdiyar, A, Fallahpour, A and Olanipekun, A O (2022) A Coupled Genetic Programming Monte Carlo Simulation–Based Model for Cost Overrun Prediction of Thermal Power Plant Projects. Journal of Construction Engineering and Management, 148(08).
Koo, H J and O’Connor, J T (2022) A Strategy for Building Design Quality Improvement through BIM Capability Analysis. Journal of Construction Engineering and Management, 148(08).
Le, C, Jeong, H D, Damnjanovic, I and Bukkapatnam, S (2022) Pareto Principle in Scoping-Phase Cost Estimating: A Multiobjective Optimization Approach for Selecting and Applying Optimal Major Work Items. Journal of Construction Engineering and Management, 148(08).
Lee, C, Chong, H, Tanko, B L and Klufallah, M (2022) Effect between Trust in Communication Technology and Interorganizational Trust in BIM-Enabled Projects. Journal of Construction Engineering and Management, 148(08).
Lee, G H, Kim, J I, Koo, C and Kim, T W (2022) Automated Generation of Precast Concrete Slab Stacks for Transportation in Offsite Construction Projects. Journal of Construction Engineering and Management, 148(08).
Liu, Y, Yao, F, Ji, Y, Tong, W, Liu, G, Li, H X and Hu, X (2022) Quality Control for Offsite Construction: Review and Future Directions. Journal of Construction Engineering and Management, 148(08).
Mmereki, D and Brouwer, D (2022) Application of Innovative Materials and Methods in Green Buildings and Associated Occupational Exposure and Health of Construction Workers: A Systematic Literature Review. Journal of Construction Engineering and Management, 148(08).
Simmons, D R, Polmear, M, Bae, H and McCall, C (2022) Applying a New Lens: Using Photo Elicitation in Construction Engineering Management Research. Journal of Construction Engineering and Management, 148(08).
Son, J, O’Brien, W J and Thomas, S R (2022) Recommended Practices for Effective Management of Academia–Industry Collaborative Research Teams in Construction Management. Journal of Construction Engineering and Management, 148(08).
Wang, Y, Thangasamy, V K, Tiong, R L K and Zhang, L (2022) Improved Workflow for Precast Element Design Based on BIM and Lean Construction. Journal of Construction Engineering and Management, 148(08).
Xia, P, Xu, F, Zhou, T and Du, J (2022) Benchmarking Human versus Robot Performance in Emergency Structural Inspection. Journal of Construction Engineering and Management, 148(08).
Zarghami, S A (2022) Prioritizing Construction Activities: Addressing the Flaws of Schedule-Based Indexes. Journal of Construction Engineering and Management, 148(08).