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In the face of diverse and conflicting factors affecting emergency water supply (EWS) decisions, ensuring sufficient drinking water provision for communities emerges as a critical and intricate challenge. Compounding this complexity is the presence of vague and imprecise data, complicating the evaluation and selection process. To tackle these challenges, this study introduces an extended fuzzy multi-criteria group decision-making (FMCGDM) model, leveraging compromise solutions and relative preference relations, specifically tailored for EWS situations. The proposed model employs linguistic variables with multiple experts’ judgements to rate the alternatives versus conflicting criteria and assign weight to these criteria. By utilizing triangular fuzzy numbers, the model effectively handles information imprecision, enabling nuanced evaluations and distinguishing among potential alternatives. Employing a relative preference relation, the model computes distance values between alternatives and ideal or anti-ideal solutions, aiding in decision-making. Finally, the practical application and computational effectiveness of the model are demonstrated through a real-life case study on EWS in Iran. The results show that the mobile water treatment units and packaged water alternatives received the highest score, placing first and second in the order ranking, respectively, while the existing distribution systems were deemed most inappropriate for the EWS situation in the case study.
In the face of diverse and conflicting factors affecting emergency water supply (EWS) decisions, ensuring sufficient drinking water provision for communities emerges as a critical and intricate challenge. Compounding this complexity is the presence of vague and imprecise data, complicating the evaluation and selection process. To tackle these challenges, this study introduces an extended fuzzy multi-criteria group decision-making (FMCGDM) model, leveraging compromise solutions and relative preference relations, specifically tailored for EWS situations. The proposed model employs linguistic variables with multiple experts’ judgements to rate the alternatives versus conflicting criteria and assign weight to these criteria. By utilizing triangular fuzzy numbers, the model effectively handles information imprecision, enabling nuanced evaluations and distinguishing among potential alternatives. Employing a relative preference relation, the model computes distance values between alternatives and ideal or anti-ideal solutions, aiding in decision-making. Finally, the practical application and computational effectiveness of the model are demonstrated through a real-life case study on EWS in Iran. The results show that the mobile water treatment units and packaged water alternatives received the highest score, placing first and second in the order ranking, respectively, while the existing distribution systems were deemed most inappropriate for the EWS situation in the case study.
The middle route of the South-to-North Water Diversion Project is one of the crucial frameworks of China’s water network and an essential channel for water resource allocation in North China. The safe operation of the project has a huge impact on regional economic development, social stability and other aspects. The objectives of this research are to improve the disposal efficiency of all kinds of accidents during the operation of the Middle Route of the South-to-North Water Diversion Project, reduce people’s property losses and ensure the safety of water supply along the line. This paper will put forward a new emergency decision-making method based on case-based reasoning technology and prospect theory. The method is divided into two parts: (1) Collecting the historical case information and building the case library. The frame representation in the case-based reasoning technology is used to describe the characteristics of historical cases and adopt the two-level method of historical cases fast retrieval and similarity fuzzy matching retrieval to complete the preliminary selection of emergency plans; (2) The decision-making and optimization model of disposal plans based on prospect theory, namely, using the value function and probability weight classification to measure the prospect value of similar schemes and selecting the optimal disposal scheme, in order to improve the science and rationality of the decision-making results. Finally, examples are taken to verify the feasibility and effectiveness of the method.
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