Modification of the Best–Worst and MABAC methods: A novel approach based on interval-valued fuzzy-rough numbers

Pamučar, Dragan; Petrović, Ivan; Ćirović, Goran

doi:10.1016/j.eswa.2017.08.042

Cited by 280 publications

(137 citation statements)

References 61 publications

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“…The elementary concept of this method can be realized in the explanation of the distance of criterion function of each alternative from the border approximation area. In this section, six easy steps to execute MABAC method are presented as follows [36][37][38][39]:…”

Section: Mabac Methodsmentioning

confidence: 99%

A Novel Hybrid Method for Non-Traditional Machining Process Selection Using Factor Relationship and Multi-Attributive Border Approximation Method

Chatterjee

Mondal²,

Boral

et al. 2017

FU Mech Eng

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Section: Mabac Methodsmentioning

confidence: 99%

A Novel Hybrid Method for Non-Traditional Machining Process Selection Using Factor Relationship and Multi-Attributive Border Approximation Method

Chatterjee

Mondal²,

Boral

et al. 2017

FU Mech Eng

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“…In the paper [94], the authors use a rough TOPSIS approach for failure mode and effects analysis in uncertain environments. The combination of rough AHP and MABAC method proposed in [95][96][97], and is used in [98] for selection of medical tourism sites. The combination of interval rough AHP and GIS is proposed for flood hazard mapping [99].…”

Section: Criteria Referencesmentioning

confidence: 99%

Novel Integrated Multi-Criteria Model for Supplier Selection: Case Study Construction Company

et al. 2017

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Supply chain presents a very complex field involving a large number of participants. The aim of the complete supply chain is finding an optimum from the aspect of all participants, which is a rather complex task. In order to ensure optimum satisfaction for all participants, it is necessary that the beginning phase consists of correct evaluations and supplier selection. In this study, the supplier selection was performed in the construction company, on the basis of a new approach in the field of multi-criteria model. Weight coefficients were obtained by DEMATEL (Decision Making Trial and Evaluation Laboratory) method, based on the rough numbers. Evaluation and the supplier selection were made on the basis of a new Rough EDAS (Evaluation based on Distance from Average Solution) method, which presents one of the latest methods in this field. In order to determine the stability of the model and the applicability of the proposed Rough EDAS method, an extension of the COPRAS and MULTIMOORA method by rough numbers was also performed in this study, and the findings of the comparative analysis were presented. Besides the new approaches based on the extension by rough numbers, the results are also compared with the Rough MABAC (MultiAttributive Border Approximation area Comparison) and Rough MAIRCA (MultiAttributive Ideal-Real Comparative Analysis). In addition, in the sensitivity analysis, 18 different scenarios were formed, the ones in which criteria change their original values. At the end of the sensitivity analysis, SCC (Spearman Correlation Coefficient) of the obtained ranges was carried out, confirming the applicability of the proposed approaches.

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“…Additionally, the Rough BWM makes it possible to bridge the existing gap that exists in the BWM methodology by applying a new approach in treating imprecision that is based on RN. This approach has been used in several studies in a very short time [53][54][55], therefore its complete algorithm has not been shown in this paper. The Rough BWM model in [53] is used to determine weight coefficients of the criteria for location selection for wind farms, while in [54], it is used to determine the importance of the criteria for selecting wagons for a logistics company.…”

Section: Proposed Methodologymentioning

confidence: 99%

“…The Rough BWM model in [53] is used to determine weight coefficients of the criteria for location selection for wind farms, while in [54], it is used to determine the importance of the criteria for selecting wagons for a logistics company. Interval Rough fuzzy BWM has been applied in [55] to a study of the optimal selection of firefighting helicopters. The Rough BWM is expected to be increasingly used in the future, which is one of the reasons for its application in this paper.…”

Section: Proposed Methodologymentioning

confidence: 99%

The Location Selection for Roundabout Construction Using Rough BWM-Rough WASPAS Approach Based on a New Rough Hamy Aggregator

et al. 2018

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An adequately functionally located traffic infrastructure is an important factor in the mobility of people because it affects the quality of traffic, safety and efficiency of carrying out transportation activities. Locating a roundabout on an urban network is an imperative for road engineering to address traffic problems such as reduction of traffic congestion, enhancement of security and sustainability, etc. Therefore, this paper evaluates potential locations for roundabout construction using Rough BWM (Best Worst Method) and Rough WASPAS (Weighted Aggregated Sum Product Assessment) models. Determination of relative criterion weights on the basis of which the potential locations were evaluated was carried out using the Rough BWM method. In this paper, in order to enable the most precise consensus for group decision-making, a Rough Hamy aggregator has been developed. The main advantage of the Hamy mean (HM) operator is that it can capture the interrelationships among multi-input arguments and can provide DMs more options. Until now, there is no research based on HM operator for aggregating imprecise and uncertain information. The obtained indicators are described through eight alternatives. The results show that the fifth and sixth alternatives are the locations that should have a priority in the construction of roundabouts from the perspective of sustainable development, which is confirmed throughout changes of parameter k and with comparing to other methods in the sensitivity analysis.

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Modification of the Best–Worst and MABAC methods: A novel approach based on interval-valued fuzzy-rough numbers

Cited by 280 publications

References 61 publications

A Novel Hybrid Method for Non-Traditional Machining Process Selection Using Factor Relationship and Multi-Attributive Border Approximation Method

A Novel Hybrid Method for Non-Traditional Machining Process Selection Using Factor Relationship and Multi-Attributive Border Approximation Method

Novel Integrated Multi-Criteria Model for Supplier Selection: Case Study Construction Company

The Location Selection for Roundabout Construction Using Rough BWM-Rough WASPAS Approach Based on a New Rough Hamy Aggregator

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