A multi-objective optimization design approach for prefabricated components such as columns, beams, slabs, walls and stairs in prefabricated buildings using ant colony algorithm is proposed to minimize cost, duration and carbon emissions in this paper. The proposed approach takes cost, duration, and carbon emissions as objective functions, the construction technologies of cast-in-place and prefabricated components as variables, prefabrication rate as constraints, and the ant colony algorithm as a solution tool, to minimize the cost, duration, and carbon emissions of prefabricated buildings. The validity of the proposed approach was verified by applying it to the multi-objective optimization design of a three-story frame structure. The results showed that:(1) Compared to all cast-in-place buildings, the prefabricated building under the baseline scenario achieves a reduction of 0.42% in cost, 19.05% in duration, and 13.49% in carbon emissions. (2) The main factor influencing the optimal combination of prefabricated building components is the incremental benefit of cost, duration, and carbon emissions resulting from changes in sub-target weight and prefabrication rate. The weight coefficients of each sub-objective determine “how” the construction technologies of the components is selected, while the prefabrication rate determines “how much” of the construction technologies is chosen. (3) Under four scenarios with different weighting coefficients, the optimized solution for prefabricated buildings compared to cast-in-place construction shows maximum reductions of 1.26% in cost, 27.89% in duration, and 18.4% in carbon emissions. The proposed approach provides an effective pathway for the transformation from cast-in-place construction to prefabricated construction and promotes sustainable development in the building industry.

The aim of this study is to comprehensively evaluate the economic network patterns and their influencing factors of the Guangdong–Hong Kong–Macao Greater Bay Area (GHMGBA) in China, considering population scale, economic development level, and land-resource endowment. By employing a modified gravity model and a social-network method, we quantitatively analyzed urban agglomeration integrity indices, such as network density, edge–core structure, cohesive-subgroup index, and urban individual index (e.g., centrality degree) of this region, encompassing nine cities in Guangdong Province and two special administrative regions. The results revealed significant changes in the economic network patterns within the GHMGBA over time. Furthermore, the quadratic assignment procedure correlation analysis index was used to identify the various factors affecting the strength of the economic interaction. The findings demonstrated an annual increase in the strength of economic interaction between cities and regions within the GHMGBA over the past 20 years, along with the emergence of a polycentric economic development pattern. The results also suggest that the spatial location and level of economic development are key determinants influencing the strength of economic linkages in this area. This study supports the conclusion that deepening exchanges and cooperation among core cities, bolstering economic development in sub-core cities, and facilitating the construction of an integrated regional transportation network will expedite the process of economic integration.

The burgeoning urbanization of major cities has precipitated a critical examination of deep foundation pit projects, with escalating costs, protracted construction phases, complex site conditions, and specialized technical requirements. Selecting the optimal design scheme from multiple alternatives in a multiattribute decision‐making environment poses a significant challenge. This study presents a novel model tailored for the design of deep foundation pits in design‐build (DB) contracting projects. The model combines multiattribute ideal point theory with the analytic hierarchy process to evaluate 22 key factors and their uncertainties. It computes the deviations of potential design schemes from ideal benchmarks across all considered attributes. By employing the lexicographic hierarchy aggregation operator, the model aggregates group‐level deviations and linguistically weighted evaluations to calculate a comprehensive score for each design scheme. This approach aids in identifying the most suitable design to meet the deep foundation requirements of DB projects. The effectiveness of the model is demonstrated through its application in the decision‐making process for a commercial hotel’s deep foundation pit design scheme. The empirical findings affirm the model’s ability to identify critical factors and accurately assess their impact on engineering design decisions in DB contracting projects. Among the four evaluated designs, the continuous retaining wall scheme achieved the lowest group deviation score, marking it as the preferred option. Consequently, this research offers a robust framework for making informed decisions in the design of deep foundation pits within DB contracting projects, effectively handling the complexities of uncertain linguistic evaluations and the collaboration of multiple attributes.

Prefabricated buildings face greater and different prefabricated components throughout their entire lifecycle, leading to a significant increase in management difficulty. This article proposes an evaluation method based on a multi-layer complex network model combined with an improved topsis. Firstly, by combining relevant regulations, literature, and engineering experience, the factors affecting the connection of components in prefabricated building are identified and the relationships between these factors are clarified to construct a multi-layered complex network model. Secondly, complex network theory is applied to calculate and analyze the importance evaluation indicators of the model nodes. Finally, the nodes are evaluated using the entropy weight optimization topsis method, and key nodes are selected based on the comprehensive importance evaluation value, and simulation verification is carried out by attacking the nodes. A specific model is constructed and analyzed using a building in Shenzhen, Guangdong Province as an example. The study shows that:(1) By analyzing key importance evaluation metrics such as node degree, betweenness centrality, and closeness centrality, the critical nodes identified for the project are “G2,” “G1,” “S24,” and “Q1”; (2) According to the comprehensive evaluation results using the improved topsis method, quality issues are the core cause of connection problems in prefabricated components, with the construction phase being the peak period for such issues; (3) The critical nodes play a significant role in maintaining the coordination and robustness of multi-layer complex networks, and the failure of these critical nodes undermines the network’s cohesion and synergy. This study provides new insights and methods for the evaluation and management of prefabricated construction.