Resource-constrained project scheduling for construction dust emission reduction

Construction dust is a primary source of urban particulate matter pollution, posing a significant threat to public health and the urban environment. Based on the fugitive emission characteristics of construction dust, this study proposes a novel control method. Unlike existing research that relies on changing activity execution modes to reduce environmental impact, the core of this method lies in leveraging dynamic variations of meteorological conditions to mitigate construction dust pollution solely by optimizing activity execution times. Building on this, the study introduces a novel Resource-Constrained Project Scheduling Problem with Construction Dust Emission Reduction (RCPSP-CDER). By introducing a piecewise linear function to characterize the time-varying attributes of the meteorology-driven dust emission factor, a bi-objective optimization model for project duration and dust emissions is established. Two complementary solution approaches are developed: an 𝜀 -constraint Constraint Programming exact method ( 𝜀 C-CP) and an NSGA-II metaheuristic. The high-rise building case study reveals that significant reductions in construction dust emissions can be achieved through scheduling optimization, even under resource constraints and with no extension to project duration or increase in cost. Sensitivity analysis reveals the impact of meteorological conditions and resource capacity on the emission reduction potential. Computational experiments on PSPLIB benchmark instances across four scales show that 𝜀 C-CP attains solution quality comparable to NSGA-II on small-scale instances and recovers the exact Pareto front on a subset of them, thereby serving as a reliable benchmark; on medium- and large-scale instances, NSGA-II consistently outperforms 𝜀 C-CP in both Pareto front quality and computational efficiency. This study provides project managers with a robust quantitative decision-making tool to achieve dust reduction targets under practical engineering constraints.