Risk analysis of cutting system under intuitionistic fuzzy environment

Kushwaha, Dinesh Kumar; Panchal, Dilbagh; Sachdeva, Anish

doi:10.31181/rme200101162k

Cited by 90 publications

(60 citation statements)

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“…To improve the complexity of the model of multi-criteria decision making [54][55][56][57][58][59], the RADERIA model is proposed based on the relation between the alternatives. Relations between the alternatives are defined according to the reference point (ideal and anti-ideal alternatives) which enables comprehensive information on alternatives and making an objective decision.…”

Section: Discussion Of Resultsmentioning

confidence: 99%

Evaluation of Human Resources in Transportation Companies Using Multi-Criteria Model for Ranking Alternatives by Defining Relations between Ideal and Anti-Ideal Alternative (RADERIA)

et al. 2021

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Multi-criteria decision-making methods (MCDM) represent a very powerful tool for making decisions in different areas. Making a rational and reliable decision, while respecting different factors, is a challenging and difficult task; MCDM models have a great impact on achieving this goal. In this paper, a new MCDM technique is presented—ranking alternatives by defining relations between the ideal and anti-ideal alternative (RADERIA), which was tested for the evaluation of human resources (HR) in a transportation company. The RADERIA model has three key advantages that recommend it for future use: (1) the RADERIA model has a new approach for data normalization that enables defining the normalization interval according to the judgments of a decision-maker; (2) an adaptive model for data normalization of the RADERIA model allows tough conversion into various forms of decreasing functions (linear, quadratic equation, etc.); and (3) the resistance of the RADERIA model to the rank reversal problem. Furthermore, in many simulations, the RADERIA method has shown stability when processing a larger number of datasets. This was also confirmed by a case study with 36 alternatives, as considered in this paper. The results and verification of the proposed new method were acquired through a comprehensive verification of the complexity of the results. The complexity of the results was executed through (1) comparison with four other multi-criteria methods, (2) checking the resistance of the RADERIA model to the rank reversal problem, and (3) the analysis of the impact of changes in the measurement scale on the ranking results.

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Section: Discussion Of Resultsmentioning

confidence: 99%

Evaluation of Human Resources in Transportation Companies Using Multi-Criteria Model for Ranking Alternatives by Defining Relations between Ideal and Anti-Ideal Alternative (RADERIA)

et al. 2021

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“…Initially, the limitations of the model must be circumvented. Later, the proposed model could be flexibly used for other crucial decision‐making areas, such as logistic 56 decision, agrodecision, 57 tool/equipment decision, 58 and other areas. Finally, plans are being made to integrate concepts, such as rough sets 59 and machine learning with MCDM models for proper recommendation and decision‐making.…”

Section: Discussionmentioning

confidence: 99%

Assessment of cloud vendors using interval‐valued probabilistic linguistic information and unknown weights

et al. 2021

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Cloud vendors (CVs) play an indispensable role in the development of IT sectors and industry 4.0. Many CVs evolve every day, and a systematic selection of these is becoming substantial for organizations. Literature studies have shown that multicriteria decision‐making (MCDM) is a powerful tool for systematic selection. However, the major issue with the state‐of‐the‐art models is that they do not effectively represent uncertainty. Moreover, the personalized selection of CVs based on user queries is not prominent in an MCDM context. In this paper, to circumvent these issues, a new decision framework is proposed that utilizes a generalized preference style called interval‐valued probabilistic linguistic term set (IVPLTS). This preference style considers occurring probability values as interval numbers instead of a single precise value, which provides flexibility during preference elicitation. Initially, missing values are imputed systematically by using a case‐based method. Then, the consistency of these preferences is checked using Cronbach's alpha coefficient, and the inconsistent preferences are repaired rationally by using an iterative method. A programming model is proposed for determining the weights of the evaluation criteria. Furthermore, Maclaurin symmetric mean (MSM) is extended to IVPLTS for aggregating preferences from each expert. The interval‐valued probabilistic linguistic comprehensive (IVPLC) method is proposed for prioritizing CVs in a personalized manner. Finally, the framework's practicality is validated by using a case study of CV selection for an academic institution; strengths and weaknesses of the framework are conferred by comparison with extant CV selection models.

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“…x R y means that x and y are connected by a fuzzy relation R (x, y). If we denote "x is A" by the fuzzy set A, then the meaning of "y is B" can be calculated as (Kushwaha et al, 2020):…”

Section: Fuzzy Logic Systemmentioning

confidence: 99%

Model for selecting a route for the transport of hazardous materials using a fuzzy logic system

Milošević¹,

Pamučar²,

Chatterjee³

2021

Vojnotehnički glasnik

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Introduction/purpose: The paper presents a model for the selection of a route for the transport of hazardous materials using fuzzy logic systems, as a type of artificial intelligence systems. The system presented in the paper is a system for assistance in the decisionmaking process of the traffic service authorities when choosing one of several possible routes on a particular path when transporting hazardous materials. Methods: The route evaluation is performed on the basis of five criteria. Each input variable is represented by three membership functions, and the output variable is defined by five membership functions. All rules in a fuzzy logic system are determined by applying the method of weight premise aggregation (ATPP), which allows the formation of a database based on experience and intuition. Based on the number of input variables and the number of their membership functions, the basic base of 243 rules is defined. Three experts from the Ministry of Defense were interviewed to determine the weighting coefficients of the membership functions, and the values of the coefficients were determined using the Full Consistency Method (FUCOM). Results: A user program which enables the practical application of this model has been created for the developed fuzzy logic system. Conclusion: The user platform was developed in the Matlab 2008b software package.

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Risk analysis of cutting system under intuitionistic fuzzy environment

Cited by 90 publications

References 0 publications

Evaluation of Human Resources in Transportation Companies Using Multi-Criteria Model for Ranking Alternatives by Defining Relations between Ideal and Anti-Ideal Alternative (RADERIA)

Evaluation of Human Resources in Transportation Companies Using Multi-Criteria Model for Ranking Alternatives by Defining Relations between Ideal and Anti-Ideal Alternative (RADERIA)

Assessment of cloud vendors using interval‐valued probabilistic linguistic information and unknown weights

Model for selecting a route for the transport of hazardous materials using a fuzzy logic system

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