Abstract
Construction projects are often executed in complex environments, and various uncertain factors (e.g., bad weather, machine breakdown) prolong activity duration in practice, which may cause project completion delays or profit reduction. Moreover, previous studies often optimized net present value or robustness in project scheduling separately, they neglected the linkage between the value of obtaining NPV and the capacity of tackling uncertainties in a project schedule. To achieve optimal profit and enhance the stability of a project schedule simultaneously, this study proposes a bi-objective optimization for resource-constrained robust construction project scheduling problem (RCRCPSP), which aims at optimizing NPV and robustness, and builds a bi-objective optimization model for the RCRCPSP based on five typical cash flow models. Then an ε-constraints procedure embedded with a genetic algorithm is proposed to solve the model. The ε-constraints procedure performs better than the multi-objective genetic algorithm proposed by the previous study through case study. Furthermore, the findings demonstrate that a trade-off relationship exists between NPV and robustness, and cash flow models have little impact on robustness, while the relaxed deadline can improve a project schedule with high robustness. The fruits of this study can help contractors balance the NPV and the robustness in an indeterministic environment.
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Acknowledgments
This work was supported by the <Special Fund of Science Research of Sichuan Agricultural University> under Grant [No. 2121993518; 2221993535].
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Liu, W., Ge, L., Qu, C. et al. Bi-objective Optimization for Resource-constrained Robust Construction Project Scheduling. KSCE J Civ Eng 28, 15–28 (2024). https://doi.org/10.1007/s12205-023-0633-8
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DOI: https://doi.org/10.1007/s12205-023-0633-8