Novel approach to group multi-criteria decision making based on interval rough numbers: Hybrid DEMATEL-ANP-MAIRCA model

Pamuar, Dragan; Mihajlovi, Milan; Obradovi, Radojko; Atanaskovi, Predrag

doi:10.1016/j.eswa.2017.06.037

Cited by 199 publications

(125 citation statements)

References 92 publications

(47 reference statements)

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“…For ranging of alternatives, the following methods were used: R'MAIRCA [104], R'MULTIMOORA (extended in this research), R'COPRAS (extended in this research), R'MABAC [98]. Combining rough AHP and rough DEMATEL, which were used for the evaluation of the criteria weight with R'MAIRCA, R'MULTIMOORA, R'Ctable OPRAS, R'MABAC and R'EDAS models, ten hybrid models were developed (in total), which are shown in Table 14.…”

Section: Sensitivity Analysis and Discussionmentioning

confidence: 99%

“…Rough AHP and rough TOPSIS approach are also used in the work of Song et al [100]. From its beginnings until nowadays, the theory of rough sets has evolved through solving many problems by using rough sets [101][102][103][104][105], and through the use of rough numbers as in [106,107], while in the work [5], the authors use a grey based rough set. Supplier selection can also be evaluated by using a new rough set approach which has been developed by Chai and Liu [108] and, according to the authors, provides stable results.…”

Section: Criteria Referencesmentioning

confidence: 99%

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

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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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Section: Sensitivity Analysis and Discussionmentioning

confidence: 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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“…The model presented in the paper is solved by using the following methods: rough SAW [39], rough EDAS [35], rough MABAC [32], rough VIKOR [47], rough MAIRCA [43] and rough MULTIMOORA [35]. Their results and comparison with the rough WASPAS approach are shown in Figure 2.…”

Section: Sensitivity Analysismentioning

confidence: 99%

“…Since rough set theory deals solely with internal knowledge, i.e., operational data, there is no need to rely on assumption models. In other words, when applying rough sets, only the structure of the given data is used instead of various additional/external parameters [43]. Duntsch and Gediga [44] believe that the logic of rough set theory is based solely on data that speak for themselves.…”

Section: Applications Of Rough Sets In Multiple Criteria Decision Makmentioning

confidence: 99%

A Novel Rough WASPAS Approach for Supplier Selection in a Company Manufacturing PVC Carpentry Products

et al. 2018

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Abstract:The decision-making process requires the prior definition and fulfillment of certain factors, especially when it comes to complex areas such as supply chain management. One of the most important items in the initial phase of the supply chain, which strongly influences its further flow, is to decide on the most favorable supplier. In this paper a selection of suppliers in a company producing polyvinyl chloride (PVC) carpentry was made based on the new approach developed in the field of multi-criteria decision making (MCDM). The relative values of the weight coefficients of the criteria are calculated using the rough analytical hierarchical process (AHP) method. The evaluation and ranking of suppliers is carried out using the new rough weighted aggregated sum product assessment (WASPAS) method. In order to determine the stability of the model and the ability to apply the developed rough WASPAS approach, the paper analyzes its sensitivity, which involves changing the value of the coefficient λ in the first part. The second part of the sensitivity analysis relates to the application of different multi-criteria decision-making methods in combination with rough numbers that have been developed in the very recent past. The model presented in the paper is solved by using the following methods: rough Simple Additive Weighting (SAW), rough Evaluation based on Distancefrom Average Solution (EDAS), rough MultiAttributive Border Approximation area Comparison (MABAC), rough Višekriterijumsko kompromisno rangiranje (VIKOR), rough MultiAttributiveIdeal-Real Comparative Analysis (MAIRCA) and rough Multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA). In addition, in the third part of the sensitivity analysis, the Spearman correlation coefficient (SCC) of the ranks obtained was calculated which confirms the applicability of all the proposed approaches. The proposed rough model allows the evaluation of alternatives despite the imprecision and lack of quantitative information in the information-management process.

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“…For this purpose, the following methods were used: Rough SAW (Simple Additive Weighting) [54], Rough EDAS (Evaluation based on Distance from Average Solution) [47], Rough MABAC (Multi-Attributive Border Approximation Area Comparison) [74] and Rough TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) [75], Rough MAIRCA (Multi-Attributive Ideal-Real Comparative Analysis) [76] and Rough VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) [77].…”

Section: Sensitivity Analysismentioning

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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Novel approach to group multi-criteria decision making based on interval rough numbers: Hybrid DEMATEL-ANP-MAIRCA model

Cited by 199 publications

References 92 publications

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

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

A Novel Rough WASPAS Approach for Supplier Selection in a Company Manufacturing PVC Carpentry Products

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

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