1,010 research outputs found

    Algorithms for probabilistic uncertain linguistic multiple attribute group decision making based on the GRA and CRITIC method: application to location planning of electric vehicle charging stations

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    Electric vehicles (EVs) could be regarded as one of the most innovative and high technologies all over the world to cope with the fossil fuel energy resource crisis and environmental pollution issues. As the initiatory task of EV charging station (EVCS) construction, site selection play an important part throughout the whole life cycle, which is deemed to be multiple attribute group decision making (MAGDM) problem involving many experts and many conflicting attributes. In this paper, a grey relational analysis (GRA) method is investigated to tackle the probabilistic uncertain linguistic MAGDM in which the attribute weights are completely unknown information. Firstly, the definition of the expected value is then employed to objectively derive the attribute weights based on the CRiteria Importance Through Intercriteria Correlation (CRITIC) method. Then, the optimal alternative is chosen by calculating largest relative relational degree from the probabilistic uncertain linguistic positive ideal solution (PULPIS) which considers both the largest grey relational coefficient from the PULPIS and the smallest grey relational coefficient from the probabilistic uncertain linguistic negative ideal solution (PULNIS). Finally, a numerical case for site selection of electric vehicle charging stations (EVCS) is designed to illustrate the proposed method. The result shows the approach is simple, effective and easy to calculate

    PDHL-EDAS method for multiple attribute group decision making and its application to 3D printer selection

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    With the rapid development of 3D printing technology, 3D printers are manufactured based on the principle of 3D printing technology are more and more widely used in the manufacturing industry. Choosing high quality 3D printers for industrial production is of great significance to the economic growth of enterprises. In fact, it is difficult to select the most optimal 3D printers under a single and simple standard. Therefore, this paper establishes the probabilistic double hierarchy linguistic EDAS (PDHL-EDAS) method for the multiple attribute group decision making (MAGDM). Then the CRITIC model is introduced to derive objective weight and the cumulative prospect theory is leaded into obtain the cumulative weight of PDHLTS. In addition, whatā€™s more, the PDHL-EDAS method is built and applied to the choice of high-quality 3D printer. Finally, compared with the available MAGDM methods under PDHLTS, the built method is proved to be scientific and effective. First published online 15 December 202

    Wasserstein distance-based probabilistic linguistic TODIM method with application to the evaluation of sustainable rural tourism potential

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    The evaluation of sustainable rural tourism potential is a key work in sustainable rural tourism development. Due to the complexity of the rural tourism development situation and the limited cognition of people, most of the assessment problems for sustainable rural tourism potential are highly uncertain, which brings challenges to the characterisation and measurement of evaluation information. Besides, decision-makers (DMs) usually do not exhibit complete rationality in the practical evaluation process. To tackle such problems, this paper proposes a new behaviour multi-attribute group decision-making (MAGDM) method with probabilistic linguistic terms sets (PLTSs) by integrating Wasserstein distance measure into TODIM (an acronym in Portuguese of interactive and multicriteria decision making) method. Firstly, a new Wasserstein-based distance measure with PLTSs is defined, and some properties of the proposed distance are developed. Secondly, based on the correlation coefficient among attributes and standard deviation of each attribute, an attribute weight determination method (called PL-CRITIC method) is proposed. Subsequently, a Wasserstein distance-based probabilistic linguistic TODIM method is developed. Finally, the proposed method is applied to the evaluation of sustainable rural tourism potential, along with sensitivity and comparative analyses, as a means of illustrating the effectiveness and advantages of the new method

    Expanding Grey Relational Analysis With the Comparable Degree for Dual Probabilistic Multiplicative Linguistic Term Sets and Its Application on the Cloud Enterprise

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    Under the cloud trend of enterprises, how do traditional businesses get on the cloud becomes a worth pondering question. To help those traditional businesses that have no experience to dispel the clouds and see the sun as soon as possible, we are planning to choose one corporation with rich experience to take them into the cloud market. The quintessence of dual probabilistic linguistic term sets (DPLTSs) is that it uses the combination of several linguistic terms and their proportions to reveal decision information by opposite angles. This paper proposes the dual probabilistic multiplicative linguistic preference relations (DPMLPRs) based upon the dual probabilistic multiplicative linguistic term sets (DPMLTSs). Then, it de nes the comparable degree between the DPMLPRs and studies the consensus of the group DPMLPR. Moreover, it probes the expanding grey relational analysis (EGRA) under the proposed comparable degree between the DPMLTSs. After that, one example of choosing the experienced cloud cooperative partner is simulated under the dual probabilistic linguistic circumstance. Besides, the comparative analysis is performed by considering the similarity among the EGRA, TODIM, and VIKOR.Postgraduate Research and Practice Innovation Program of Jiangsu Province under Grant KYCX18_0199Scientific Research Foundation of the Graduate School of Southeast University under Grant YBJJ1832FEDER Financial Support under Grant TIN2016-75850-

    A multidimensional decision with nested probabilistic linguistic term sets and its application in corporate investment

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    With the rapid development of information, decision making problems in various fields have presented multidimensional, complex and uncertain characteristics. Nested probabilistic-numerical linguistic term set (NPNLTS) is an effective tool to describe complex information due to the nested structure and diverse variables. This paper extends the concept of NPNLTS, and defines an improved form, i.e., nested probabilistic linguistic term set (NPLTS), and then proposes a novel VIKOR method with nested probabilistic linguistic information to solve the model. Within the context of empirical corporate finance, a case study related to corporate investment decision is presented and handled by the novel VIKOR method. After that, comparative analysis is carried out considering other decision-making methods, decision coefficient in VIKOR, and weights of attributes. As a result, the proposed method not only provides a rational and effective solution, but also reveals the rule in the case when decision coefficient and weights of attributes change, respectively. Finally, we discuss the proposed method from the theoretical and application aspects with a view to guiding future research. To a certain extent, this study provides a new decision environment to deal with multidimensional problems

    Modified EDAS Method Based on Cumulative Prospect Theory for Multiple Attributes Group Decision Making with Interval-valued Intuitionistic Fuzzy Information

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    The Interval-valued intuitionistic fuzzy sets (IVIFSs) based on the intuitionistic fuzzy sets combines the classical decision method is in its research and application is attracting attention. After comparative analysis, there are multiple classical methods with IVIFSs information have been applied into many practical issues. In this paper, we extended the classical EDAS method based on cumulative prospect theory (CPT) considering the decision makers (DMs) psychological factor under IVIFSs. Taking the fuzzy and uncertain character of the IVIFSs and the psychological preference into consideration, the original EDAS method based on the CPT under IVIFSs (IVIF-CPT-MABAC) method is built for MAGDM issues. Meanwhile, information entropy method is used to evaluate the attribute weight. Finally, a numerical example for project selection of green technology venture capital has been given and some comparisons is used to illustrate advantages of IVIF-CPT-MABAC method and some comparison analysis and sensitivity analysis are applied to prove this new methods effectiveness and stability.Comment: 48 page

    Probabilistic double hierarchy linguistic alternative queuing method for real economy development evaluation under the perspective of economic financialization

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    With the development of science and technology, the new road of scientific economic and financial development has played a decisive role in supporting the financial undertaking. To accelerate the economic development, it is very important to increase the guiding role of financial undertaking in the real economy. Therefore, it is necessary to promote the development of the real economy under the perspective of economic financialization based on some actions. To judge the implementation effect of these actions, this paper develops a multiple criteria decisionmaking (MCDM) method to evaluate them. First, the decisionmaking matrices are established with the probabilistic double hierarchy linguistic term set in which the probabilities are added to all double hierarchy linguistic terms. Additionally, a weightdetermining method is developed to obtain the weight vector of criteria, and we develop a MCDM method named the probabilistic double hierarchy linguistic alternative queuing method (PDHLAQM), where the decision-making result is intuitive by a directed graph or a 0ā€“1 precedence relationship matrix. Furthermore, we apply the PDHL-AQM to solve a practical MCDM problem involving the real economy development evaluation under the perspective of economic financialization. Finally, some comparative analyses are made to show the advantages and reasonableness of the PDHL-AQM

    Dynamic reference point method with probabilistic linguistic information based on the regret theory for public health emergency decision-making

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    Group emergency decision-making is an uncertain and dynamic process, in which the decision makers may be bounded rational and have a risk appetite. To depict the vague qualitative assessments, the probabilistic linguistic term sets are employed to express the perceptions of decision makers. First, considering the regret-aversion of the decision makersā€™ psychological characteristic, the value function and the regret-rejoice function in the regret theory are modified to adapt the probabilistic linguistic information. Second, the definition and aggregation operators of the probabilistic linguistic time variable are proposed to describe and aggregate the dynamic decision information. Third, the probabilistic linguistic models based on the dynamic reference point method and the regret theory are studied to maximise the expectation-levels of alternatives at the relative time point. The proposed method is applied to select the optimal response strategy for the outbreak of COVID-19 in China. Finally, the comparative analysis is designed to verify the applicability and reasonability of the proposed method

    Green supplier selection based on CODAS method in probabilistic uncertain linguistic environment

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    Probabilistic uncertain linguistic sets (PULTSs) have widely been used in MADM or MAGDM. The CODAS method, which is a novel MADM or MAGDM tool, aims to acquire the optimal choice which have the largest Euclidean & Hamming distances from the NIS. This paper designs the probabilistic uncertain linguistic CODAS (PUL-CODAS) method with sine entropy weight. Finally, a numerical example for green supplier selection is given and the obtained results are compared with some existing models. First published online 05 February 202
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