Multicriteria Decision Making Model with Z-Numbers Based on FUCOM and MABAC model

Božanić, Darko; Tešić, Duško; Milić, Aleksandar

doi:10.31181/dmame2003019d

Cited by 61 publications

(43 citation statements)

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“…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%

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: 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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“…It involves fuzzy reliability in addition to the fuzzy restriction that enables analysts to take into account the uncertainty that occurred from the reliability of the decision-makers. Since it has more capability to describe the uncertainty, there are various approaches which are combined with Z-numbers to evaluate MCDM problems [67,68,[92][93][94][95].…”

Section: Literature Review On Methodologymentioning

confidence: 99%

Prioritization of public services for digitalization using fuzzy Z-AHP and fuzzy Z-WASPAS

Sergi

Sarı

2021

Complex Intell. Syst.

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In this paper, public services are analyzed for implementations of Industry 4.0 tools to satisfy citizen expectations. To be able to prioritize public services for digitalization, fuzzy Z-AHP and fuzzy Z-WASPAS are used in the analysis. The decision criteria are determined as reduced cost, fast response, ease of accessibility, reduced service times, increase in the available information and increased quality. After obtaining criteria weights using fuzzy Z-AHP, health care services, waste disposal department, public transportation, information services, social care services, and citizen complaints resolution centers are compared using fuzzy Z-WASPAS that is proposed for the first time in this paper. Results show that health care services have dominant importance for the digitalization among public services.

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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

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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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Multicriteria Decision Making Model with Z-Numbers Based on FUCOM and MABAC model

Cited by 61 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

Prioritization of public services for digitalization using fuzzy Z-AHP and fuzzy Z-WASPAS

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

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