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The successful diagnosis of nuclear power equipment failures plays a vital role in guaranteeing the safe operation of nuclear power systems. Failure mode and effect analysis (FMEA) is one of the most commonly used methods for identifying potential failures. However, several shortcomings associated with the conventional FMEA method limit its further application. This paper develops an extended FMEA approach based on hesitant fuzzy linguistic Z-numbers (HFLZNs). Firstly, the concept of HFLZNs is proposed to describe the evaluation information, which inherits the prominent features of the hesitant fuzzy linguistic term set and linguistic Z-numbers (LZNs). Secondly, an HFLZN assessment method is developed to determine the weights of risk factors, and the weights of experts are measured based on hesitation degree. Subsequently, considering the psychological characteristics of decision makers, Tomada de Decisão Iterativa Multicritério and LZNs are integrated to obtain the risk ranking of failure modes. Finally, the practicability of the extended FMEA method is proven by an illustrative example concerning the risk evaluation of a nuclear main pump bearing, and its robustness is verified by indepth analysis. [ABSTRACT FROM AUTHOR]

Preference relations as information representation form are widely used to manage complexity and uncertainty in practical decision-making cases. Intuitionistic trapezoidal fuzzy numbers (ITrFNs) can convey more fuzzy messages than other fuzzy numbers. This paper defines intuitionistic trapezoidal fuzzy preference relations (ITrFPRs) to adequately describe the preferences of decision makers (DMs). To optimize the decision-making selection process, this paper constructs a three-cycle decision-making selection mechanism with ITrFPRs. To build this mechanism, firstly, a possibility degree formula is presented to rank ITrFNs. Secondly, ITrFPRs, consistent ITrFPRs, acceptable consistent ITrFPRs and a new consistency index are defined. Thirdly, a novel consistency transformation method is built to elevate the consistency of ITrFPRs. Fourthly, considering the relationship between consistency conditions and priority weight, a priority weight derivation method is exploited to derive intuitionistic trapezoidal fuzzy weights. Ultimately, a three cycle selection mechanism integrated with consistency checking, consistency improvement and priority weight derivation procedures is constructed and applied into the case of trip itinerary selection. Sensitive and comparative analyses are carried out to illustrate the effectiveness and applicability of the proposed mechanism. [ABSTRACT FROM AUTHOR]

This study develops an approach that incorporates power aggregation operators with the evaluation based on distance from average solution (EDAS) method under linguistic neutrosophic situations to solve fuzzy multi-criteria group decision-making problems. Firstly, the existing operational laws and comparison methods of linguistic neutrosophic numbers (LNNs) are analysed. Secondly, the distance measurement between two LNNs is defined. Thirdly, the power-weighted averaging operator and the power-weighted geometric operator with LNNs are developed to support the decision makers' evaluation information. The models to derive the criteria weights are also constructed based on the proposed distance measurements. Finally, the EDAS method is extended to resolve group decision-making problems in the linguistic neutrosophic environment. An illustrative example of the property management company selection is given to verify the effectiveness and practicality of the proposed approach. [ABSTRACT FROM AUTHOR]

The Z-number has become a new representation of evaluation information because of its superiority in describing reliability measure. Current studies focuses mainly on the unidimensional Z-number like Z = (about 25 min, usually). Studies on multidimensional cases have not been reported. However, because people often describe things from various aspects, using only one aspect of information to describe uncertain events fully is difficult. In this paper, we propose the concept of the multidimensional Z-number, such as ((about 20 miles, about 25 min), usually) to handle complex information. For this purpose, we first define the basic operations of the multidimensional Z-number. We then propose a feasible comparison method. The effectiveness of the proposed method is demonstrated by a series of numerical examples. [ABSTRACT FROM AUTHOR]

Stock evaluation is a significant decision-making activity for investors. Due to the complexity of stock exchange market, evaluation information may be fuzzy and stochastic in the meantime. Therefore, it is essential to conduct the research on fuzzy stochastic multi-criteria decision-making (FSMCDM) methods. In this paper, at the beginning, we propose interval neutrosophic probability from the definition of neutrosophic probability. Then, a novel MCDM method is proposed with interval neutrosophic probability based on regret theory, in which criteria values are interval neutrosophic numbers (INNs). The method proposed with interval neutrosophic probability may be much better than methods using classic probability or fuzzy probability. Next, we apply the proposed method to stock selection problems and discuss the influence of parameters on ranking results. Finally, we compare regret theory with prospect theory, which is also an important theory of bounded rationality just like regret theory, to emphasize the characteristics the regret theory. Moreover, a comparative analysis is also conducted between the proposed method and existing methods under interval neutrosophic environment to demonstrate efficiency and applicability of the proposed method. [ABSTRACT FROM AUTHOR]

Under the double pressure of global energy consumption and climate change, nuclear power has become a low-carbon alternative energy source that could transform the energy structure of the globe. In the nuclear power industry, selecting suitable suppliers plays a significant role in improving the overall performance of nuclear power projects. Along with this symmetrical impact, this paper aims to develop a multistage decision-support framework to determine the optimal nuclear power equipment supplier, which is constructed in the context of Z-number information. Concretely, the Analytic Network Process (ANP) and Tomada de Decisão Iterativa Multicritério (TODIM) are extended by Z-numbers symmetrically—namely, Z-ANP and Z-TODIM. Z-ANP is first applied to analyze the symmetrical interdependence of criteria, so as to accurately determine the criterion weights. Further, the ranking of alternatives is obtained by Z-TODIM, which sufficiently considers the risk preference and psychological states of decision-makers. Finally, a practical case of nuclear-grade cable procurement in the Karachi 2-3 international nuclear power project is performed to illustrate the practicality of the proposed method, and its robustness and superiority are proven by comparing it with current representative approaches. [ABSTRACT FROM AUTHOR]

To promote the development of nuclear power project in inland China, a specialized multi-criteria decision support framework is constructed for the site selection of inland nuclear power plants in this work. The best worst method (BWM), decision-making trial and evaluation laboratory (DEMATEL), and technique for order performance by similarity to ideal solution (TOPSIS) are integrated with Z-numbers, namely Z-BWM, Z-DEMATEL, and Z-TOPSIS. Z-BWM and Z-DEMATEL are combined to produce the weights of criteria, and an extended Z-TOPSIS is utilized to determine the ranking of all alternatives. Finally, a case study is performed in Hunan province to demonstrate the practicability of the proposed decision support framework. The robustness and feasibility of the proposed method are shown by an in-depth analysis of the decision results. [ABSTRACT FROM AUTHOR]

Probabilistic interval‐valued hesitant fuzzy sets (PIV‐HFSs) are suitable for aggregating information from different groups because the probabilistic information of all the groups can be included by using interval values. Moreover, decision makers (DMs) prefer to use interval values to provide evaluation information. Furthermore, the traditional multi‐criteria group decision‐making (MCGDM) approach has some limitations, such as obtaining the DMs' weights with inappropriate methods and neglecting the interactions amongst the criteria and the psychological characteristics of DMs. Motivated by these research background, the main contents of this study are as follows. First, PIV‐HFSs are proposed, and the convex combination operation is extended into PIV‐HFSs. Second, a hybrid MCGDM approach with PIV‐HFSs is suggested that is based on the maximizing deviation method, fuzzy analytic network process (FANP) and TODIM (an acronym in Portuguese for interactive and multi‐criteria decision‐making model). Third, an evaluation case of health management centres based on the service‐specific failure mode and effect analysis (FMEA) is considered. The results show that the most crucial secondary factor is frequency (0.35775) and that the most serious failure mode is the inaccurate check‐in. The results demonstrate that the proposed model can evaluate service quality effectively and that it performs better than other methods. [ABSTRACT FROM AUTHOR]

Abstract The sustainability challenge is increasingly driving the adoption of supercritical water gasification (SCWG) technology to ensure the elimination and recovery of pollution produced by sewage sludge treatment (SST). Risk evaluation by failure mode and effects analysis (FMEA) plays a crucial role in guaranteeing the reliability and safety of SCWG systems. However, some limitations in existing FMEA methods need to be ameliorated. Multiple risk factors are involved in prioritizing risk levels for failure modes in SCWG systems, it is essential a multiple criteria decision making (MCDM) process, in which overall assessments of failure modes should be provided according to their performances from several points during a system operation period. Due to differences in knowledge backgrounds and experiences, FMEA team members prefer to utilize multi-granular linguistic term sets to express their assessments of system risk. A hybrid risk evaluation model by FMEA is exploited with multi-granular linguistic distribution assessments to suit practical case. Best-worst and maximizing derivation methods are adopted to determine subjective and objective combined weights for distinguishing the importance of risk factors. Complex proportional assessment method is used to prioritize failure modes for explicitly and effectively reflecting the risk level of each failure mode. The proposed model is applied in a practical case of an SCWG system used in SST. Results derived from comparative and sensitivity analyses fully demonstrate the reliability and validity of the model. [ABSTRACT FROM AUTHOR]

Abstract Under the double pressure of global energy tightening and energy saving, new renewable energy sources, especially offshore wind power, have become considerably popular. To promote the development of offshore wind power projects, there has been an urgent push towards the research on selecting a satisfactory offshore wind power station site. However, existing methods have ignored the consensus problem embedded in the selection process. With the aim of addressing this issue, we devote our effort to developing a consensus decision framework. To this end, we employ the picture fuzzy set (PFS) to collect and describe large amounts of uncertain evaluation information for distinctive sites. Then, some relative projection models for PFSs are developed to support the determination of importance weights of groups of decision makers who are invited to evaluate the performance of alternative sites. Subsequently, a consensus reaching process is presented to guarantee that each group is satisfied with the final selection. Finally, the classical technique for order preference by similarity to an ideal solution method is extended to reasonably select the most suitable site without a subjective supply for criteria weights. A case study on the location selection of offshore wind power station illustrates the validity and applicability of the framework. Through this work, we believe that the models and methods in different phases of our framework can be valuably applicable to similar problems and significantly beneficial to the promotion of PFS theory. Highlights • Picture fuzzy sets are applied to quantify contradictory decision information. • Some relative projection models are adapted to measure similarities and weights. • Two aggregation operators are developed for fusing distinctive opinions. • A consensus reaching process is devised to assess offshore wind power station site. • An extended TOPSIS method is introduced for selecting the optimal site. [ABSTRACT FROM AUTHOR]

Faced with risks aroused by the ever-increasing expansion of industrialization and urbanization, water security sustainability takes more and more effect on balancing regional sustainability and development, especially for industrial regions. Introducing sustainability into the indicator framework of water security is an indispensable issue should be addressed. The indicators of water security sustainability in practice are measured by observation data obtained from a monitoring period. These data are commonly expressed in various forms, such as ratio and qualitative linguistic, which makes them hard to be quantified and evaluated. As multiply influential criteria are involved the water security sustainability evaluation process, it can be treated as a multi-criteria decision making problem. An appropriate evaluation framework with scientific and strategic multi-criteria decision making techniques is supposed to be constructed. This paper incorporates the dimensions related to sustainability into the indicator framework of water security sustainability. Another contribution of this paper is that it establishes an observation data conversion standard and adopts linguistic distribution assessments as information representation. Linguistic distribution assessments can capture the natural characteristics of the observation data of water security sustainability indicators. More importantly, a multistage decision support framework integrated with multi-criteria decision making techniques, such as best-worst method (BWM), decision making trial and evaluation laboratory (DEMATEL) and technique for order performance by similarity to ideal solution (TOPSIS), is constructed for water security sustainability evaluation. Then, deep analyzes about the evaluation results and influential factors are provided, thereby certifying the reliability of evaluation results and facilitating the enhancement of water security sustainability. [ABSTRACT FROM AUTHOR]

This study introduces simplified neutrosophic linguistic numbers (SNLNs) to describe online consumer reviews in an appropriate manner. Considering the defects of studies on SNLNs in handling linguistic information, the cloud model is used to convert linguistic terms in SNLNs to three numerical characteristics. Then, a novel simplified neutrosophic cloud (SNC) concept is presented, and its operations and distance are defined. Next, a series of simplified neutrosophic cloud aggregation operators are investigated, including the simplified neutrosophic clouds Maclaurin symmetric mean (SNCMSM) operator, weighted SNCMSM operator, and generalized weighted SNCMSM operator. Subsequently, a multi-criteria decision-making (MCDM) model is constructed based on the proposed aggregation operators. Finally, a hotel selection problem is presented to verify the effectiveness and validity of our developed approach. [ABSTRACT FROM AUTHOR]