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
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
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, whatās 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
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
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
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
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
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 0ā1 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
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
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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