To mitigate safety risks in subway shield construction within water-rich silty fine sand layers, a risk immunization strategy based on complex network theory was proposed. Safety risk factors were systematically identified through literature review and expert consultation, and their relationships were modeled as a complex network. Unlike traditional single-index analyses, this study integrated degree centrality, betweenness centrality, eigenvector centrality, and clustering coefficient centrality to comprehensively evaluate the importance of risk factors. Results indicated that targeted immunization strategies significantly outperformed random immunization, with degree centrality (DC) and betweenness centrality (BC) immunization demonstrating the best performance. Key risk sources included stratum stability, allowable surface deformation, surface settlement monitoring, and shield tunneling control. Furthermore, the optimal two-factor coupling immunization strategy was found to be the combination of DC and BC strategies, which provided the most effective risk prevention. This study is the first to apply complex network immunization simulation to safety risk management in subway shield construction, enhancing the risk index system and validating the impact of different immunization strategies on overall safety. The findings offer scientific guidance for risk management in complex geological conditions and provide theoretical support and practical insights for improving construction safety.
The increasing demand for efficient and sustainable last-mile delivery solutions has presented a significant challenge in the evolving landscape of e-commerce logistics. To address this issue, a systematic evaluation and prioritization of six alternative delivery methods—namely, home delivery, workplace delivery, delivery to a neighbor or acquaintance, staffed pickup points, unstaffed (automated) pickup points, and third-party drop-off locations—has been conducted. These alternatives have been assessed against a comprehensive set of criteria, including delivery time flexibility, accessibility, cost-efficiency, security, speed of service, and ease of product return. To capture the nuanced preferences and subjective judgements of stakeholders, the Fuzzy Factor Relationship (FARE) method has been employed to determine the relative importance of each criterion through a structured fuzzy logic framework. Subsequently, the Aggregated Decision-Making (ADAM) method has been applied to rank the delivery alternatives, integrating evaluations from key stakeholder groups—consumers, retailers, and logistics service providers. The findings reveal that unstaffed pickup points, particularly those leveraging automated systems, represent the most balanced and sustainable solution, offering superior performance in terms of cost-effectiveness, user accessibility, and operational flexibility. In contrast, while home delivery continues to be favored for its convenience, it remains constrained by elevated operational costs and limited scheduling flexibility. The methodological integration of Fuzzy FARE and ADAM ensures a robust and transparent decision-support mechanism that accounts for both qualitative and quantitative factors. These insights are expected to guide strategic decision-making in last-mile logistics (LML), contributing to service quality enhancement, operational cost reduction, and the advancement of environmentally responsible delivery systems. This evaluation framework offers practical relevance to e-commerce platforms, third-party logistics providers, and urban mobility planners seeking to implement scalable and customer-centric delivery models in complex urban environments.
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