In the process of site selection for waste-to-energy (WtE) projects, the public is concerned about the impact of project construction on the surrounding environment and physical health and thus resists the construction site, leading to the emergence of "Not In My Backyard" (NIMBY) risk, which hinders the implementation of WtE projects. These risks make the ambiguity and uncertainty of scheme evaluation and decision higher. In this regard, this study constructed a WtE project site selection decision framework based on comprehensive consideration of NIMBY risk. Firstly, indicators were selected from cost perception, benefit expectation, and NIMBY risk to construct a WtE project site selection indicator system. Then, based on the "Decision Making Trial and Evaluation Laboratory" (DEMATEL) and the Intuitionistic Fuzzy Multi-criteria Optimization and Compromise Solution (IFVIKOR) method, a site selection decision framework is constructed. The system takes into account the interaction between indicators and obtains a more reasonable index weight. Meanwhile, the intuitionistic fuzzy theory is used to solve the fuzziness and uncertainty in risk assessment and decision-making. Finally, the feasibility of the siting decision system was verified through case studies. The results show that the A3 in this case was considered the best location for the project. In addition, the sensitivity analysis verifies the reliability and stability of the WtE project location decision framework.

In light of the pressing global challenges related to greenhouse gas emissions from the construction industry, current evaluation systems for green building construction sustainability remain limited, often overlooking sustainability domains. This study innovatively established an evaluation framework by exploring five critical domains: environmental sustainability, economic benefits, socio-cultural impacts, technological innovation, and health and well-being. Sixteen key evaluation indicators were identified using the Delphi method, with the novel inclusion of a carbon emission reduction target achievement indicator, thereby promoting the goal of carbon neutrality in green buildings. To determine a more reasonable weight distribution, this paper combined the fuzzy analytic hierarchy process (fuzzy AHP) with the entropy weight method. Additionally, the study employed a fuzzy matter-element method enhanced by genetic algorithms for precise evaluation of green building construction sustainability. The feasibility and effectiveness of the proposed model were validated through an empirical analysis of a green building project in Beijing. The results of this research provide innovative theoretical references and practical guidelines for green building construction sustainability evaluation.