Many construction activities generate fine particles and severely threaten the physical health of construction workers. Although many dust control measures are implemented in the industry, the occupational health risks still exist. In order to improve the occupational health level, this study proposes a new method of reducing the construction dust pollution through a reasonable site layout plan. This method is based on the field measurement and dust diffusion law. The dust diffusion law can be fitted based on the field monitoring data. With diffusion law, the average dust concentration exposed to workers of different site layouts can be simulated. In addition, the cost of the dust control method is a concern for site managers. Therefore, the total transportation cost reduction is another optimization objective. Finally, the multi-objective particle swarm optimization (MOPSO) algorithm is used to search for an optimized site layout that can reduce dust pollution and transportation cost simultaneously. The result shows that average dust concentration exposed to workers and total transportation cost are significantly reduced by 60.62% and 44.3%, respectively. This paper quantifies the construction dust pollution and provides site managers with a practical solution to reduce the construction dust pollution at low cost.

In construction projects, improper quality behavior of a participant results in quality behavior risks, which can transmit to the downstream participants and may cause detrimental effects on the quality of the entity finally constructed. Controlling the transmission of quality behavior risks is the key to effectively supervising and ensuring the quality of construction projects. In this study, the effectiveness of the quality supervision system of construction projects in China was investigated by considering the transmission of quality behavior risks. A multi-player evolutionary game model consisting of the players of quality supervision of a government department, upstream participant (UP), and downstream participant (DP) was generated. By using the system dynamics theory, the game model was simulated to determine the stability of the evolutionary system and to evaluate the effectiveness of China’s current quality supervision system under different scenarios. The results showed that there is no evolutionary stable strategy (ESS) in the evolutionary system of the current quality supervision system in China and there are fluctuations in the evolution process. It revealed that high risk exists in the current quality supervision system in China. To resolve the problem of the low efficiency of the current Chinese supervision system, a dynamic penalty and incentive method is developed, which has been proven to be able to effectively control the quality behavior risks in construction projects and hence ensuring the quality of the entity finally constructed.

The water environment restoration project portfolio (WERP) selection is discussed in this paper. By complying with the analysis of the project’s multidimensional property and operation mode, this paper develops the chance constraint and the management constraint of the WERP from the perspectives of public service and enterprise operation. In addition, the multi-objective mixed integer linear programming model is constructed by combining the expectation method and the fuzzy chance constraint programming method. The results demonstrate that: (1) Our proposed method successfully circumvents the occurrence of local objective optimization within a specific confidence interval, thereby achieving a balance between economic and water environment restoration objectives; (2) including fuzzy chance constraints in our proposed method significantly diminishes the risk of exceeding the WERP capacity, thereby ensuring the effectiveness of water environment restoration by adopting a market-based approach. However, further examination of the impact of various sub-projects in WERP is necessary, along with the integration of novel evolutionary algorithms to enhance the efficiency of our model.

In Public–Private Partnership (PPP) projects, the structure of the Special Purpose Vehicle (SPV) significantly impacts the value enhancement of projects. This study conducted a quantitative analysis of value enhancement in green PPP projects under single- and Dual-Role entity models and examined existing SPV private party compositions. A quantitative model was developed to enhance the value in green PPP projects through a Dual-Role “investor–builder” entity approach, comparing it with the single-role entity model. The findings indicate that in the Dual-Role entity mode, the construction party demonstrates a greater willingness to effort, resulting in shorter construction timelines and improved economic benefits for the project company. The preferred equity range for private parties escalates with the total project investment and the extent of “political support”. Nevertheless, a disproportionately high government stake in the equity is detrimental to the value enhancement in PPPs, and excessive government regulation and control should be avoided. This quantitative model serves as a decision-making criterion for selecting the SPV mode and provides an alternative approach for evaluating PPP project performance.

The stability of a steel bracing system is one of the most important indicators by which to measure the stability of the foundation pit. Although a steel bracing system can be monitored using the axial force data, it is subject to the risk of sudden changes due to certain factors and has the characteristics of dynamic discontinuity. Therefore, safety risk management should be applied to the mutability of steel bracing systems to ensure stability. We used the steel bracing system of a foundation pit in Ningbo City, China, as the research object. First, through fault tree analysis (FTA) of the characteristics of the steel bracing system, a safety risk identification of the catastrophe risk was carried out. Second, the safety risk was standardized, and a safety risk evaluation index system was established; the validity and stability of the index system were then verified. Next, a catastrophe theory-based evaluation model was established to determine the safety risk level of the steel bracing system. Finally, a steel bracing risk management process was designed, and a safety risk response was proposed based on the results of the evaluation model. The result was that the membership function value belongs to the general risk area, which accords with the actual state of steel bracing in engineering, and subsequent safety risk response measures can be applied. The proposed method performs well in identifying the risk of sudden changes in steel bracing systems; it also rates the risk and offers response measures to ensure the stability of the steel bracing system. Additionally, this method is of significance due to its applicability in various projects.

The Chinese government’s substantial investment in water restoration has created numerous lucrative opportunities for commercial environmental restoration enterprises. Accordingly, this research study seeks to address the primary challenge faced by enterprise managers: selecting projects that fulfill both strategic imperatives and maximize economic returns. To tackle this issue, we segmented the overarching strategic period into multiple phases and studied the project portfolio from a holistic strategic period perspective. We introduced a decision model for the dynamic, sequential updating of the portfolio throughout the strategic period, emphasizing the combined benefits at each phase. This model guides the strategic selection of projects at any decision-making stage to optimize the benefits across the entire strategic duration. The multi-agent Nash Q-learning algorithm was employed for portfolio construction and updating strategies. This approach yields an optimal project portfolio for each phase of the strategy. Unlike traditional methods that predominantly focus on cumulative returns and find it challenging to accommodate strategic shifts, our proposed technique prioritizes intertwined strategic returns. It promotes project choices in tune with strategic contexts and supports ongoing adjustments to project strategies, providing invaluable guidance for decision makers. A comparison of our proposed method with other optimization strategies validated its superior performance. Furthermore, the case study described in this study confirms that our method promotes project choices in tune with strategic contexts and supports ongoing adjustments to project strategies, providing invaluable guidance for decision makers.