Sustainable supplier selection using combined FUCOM – Rough SAW model

Durmić, Elmina; Herzegovina,; Stević, Željko; Chatterjee, Prasenjit; Vasiljević, Marko; Tomašević, Milovan

doi:10.31181/rme200101034c

Cited by 139 publications

(74 citation statements)

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“…Based on the settings defined, the final nonlinear model for determining the optimal fuzzy values of the weight coefficients of the evaluation criteria can be set 12 ( , ,..., ) T n w w w .…”

Section: Conditionmentioning

confidence: 99%

“…However, unlike other subjective models, the FUCOM has shown minor deviations in the obtained values of the weights of criteria from the optimum values [9]. Moreover, the methodological procedure of the FUCOM eliminates the problem of redundancy of pairwise comparisons of criteria, which is present in some subjective models for determining the weights of criteria [10,11,12].…”

Section: Introductionmentioning

confidence: 99%

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Prioritizing the Weights of the Evaluation Criteria Under Fuzziness: the Fuzzy Full Consistency Method – Fucom-F

Pamučar

Ecer²

2020

FU Mech Eng

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Values, opinions, perceptions, and experiences are the forces that drive almost each and every kind of decision-making. Evaluation criteria are considered as sources of information used to compare alternatives and, as a result, make selection easier. Seeing their direct effect on the solution, weighting methods that most accurately determine criteria weights are needed. Unfortunately, the crisp values are insufficient to model real life problems due to the lack of complete information and the vagueness arising from linguistic assessments of decision-makers. Therefore, this paper proposes a novel subjective weighting method called the Fuzzy Full Consistency Method (FUCOM-F) for determining weights as accurately as possible under fuzziness. The most prominent feature of the proposed method is obtaining the most accurate weight values with very few pairwise comparisons. Consequently, thanks to this model, consistency and reliability of the results increase while the processing time and effort decrease. Moreover, an illustrative example related to the green supplier evaluation problem is performed. Finally, the robustness and effectiveness of the proposed fuzzy model is demonstrated by comparing it with fuzzy best-worst method (F-BWM) and fuzzy AHP (F-AHP) models.

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Section: Conditionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prioritizing the Weights of the Evaluation Criteria Under Fuzziness: the Fuzzy Full Consistency Method – Fucom-F

Pamučar

Ecer²

2020

FU Mech Eng

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“…The distribution of the weight coefficients of the membership functions should reflect reality as much as possible. In this particular case, w (xi) (j) was determined by interviewing experts and applying the FUCOM (Full Consistency Method) method (Pamučar et al, 2018), (Bozanic et al, 2019), (Fazlollahtabar et al, 2019), (Puška et al, 2019), (Erceg & Mularifović, 2019), (Durmić, 2019), (Nenadić, 2019), (Žižović & Pamucar, 2019), (Bozanic et al, 2020), (Durmić et al, 2020). Three experts were interviewed, and the results of the calculation of the weight coefficients are shown in Table 5.…”

Section: Most Often W (Xi)mentioning

confidence: 99%

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

Milošević¹,

Pamučar²,

Chatterjee³

2021

Vojnotehnički glasnik

Self Cite

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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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“…Simanaviciene and Ustinovichius 40 , suggested verification of the obtained solution by carrying out a sensitivity analysis of changes in the criteria weights. Also, some authors [45][46][47][48] stressed the need to conduct a sensitivity analysis in order to validate the MCDM results. Taking these recommendations into account, we have performed the sensitivity analysis in two stages.…”

Section: Sensitivity Analysismentioning

confidence: 99%

Application of a D Number based LBWA Model and an Interval MABAC Model in Selection of an Automatic Cannon for Integration into Combat Vehicles

2021

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A decision making procedure for selection of a weapon system involves different, often contradictory criteriaand reaching decisions under conditions of uncertainty. This paper proposes a novel multi-criteria methodology based on D numbers which enables efficient analysis of the information used for decision making. The proposed methodology has been developed in order to enable selection of an efficient weapon system under conditions when a large number of hierarchically structured evaluation criteria has to be processed. A novel D number based Level Based Weight Assessment – Multi Attributive Border Approximation area Comparison (D LBWA-MABAC) model is used for selection of an automatic cannon for integration into combat vehicles. Criteria weights are determined based on the improved LBWA-D model. The traditional MABAC method has been further developed by integration of interval numbers. A hybrid D LBWA-MABAC framework is used for evaluation of an automatic cannon for integration into combat vehicles. Nine weapon systems used worldwide have been ranked in this paper. This multicriteria approach allows decision makers to assess options objectively and reach a rational decision regarding the selection of an optimal weapon system. Validation of the proposed methodology is performed through sensitivity analysis which studies how changes in the weights of the best criterion and the elasticity coefficient affect the ranking results.

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Sustainable supplier selection using combined FUCOM – Rough SAW model

Cited by 139 publications

References 0 publications

Prioritizing the Weights of the Evaluation Criteria Under Fuzziness: the Fuzzy Full Consistency Method – Fucom-F

Prioritizing the Weights of the Evaluation Criteria Under Fuzziness: the Fuzzy Full Consistency Method – Fucom-F

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

Application of a D Number based LBWA Model and an Interval MABAC Model in Selection of an Automatic Cannon for Integration into Combat Vehicles

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