Ranking of renewable energy sources for regions in Turkey by fuzzy entropy based fuzzy COPRAS and fuzzy MULTIMOORA

Alkan, Ömer; Albayrak, Özlem

doi:10.1016/j.renene.2020.08.062

Cited by 115 publications

(31 citation statements)

References 68 publications

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“…In this phase of sensitivity analysis, six different integrated fuzzy-MADM methods were considered to check the result obtained by the fuzzy-MARCOS method. The considered MADM methods are fuzzy-WASPAS (Turskis et al 2015), fuzzy-COPRAS (Alkan et al 2020), fuzzy-MABAC (Liang et al 2019), fuzzy-CODAS (Yalçın et al 2019), fuzzy-EDAS (Polat et al 2020) and fuzzy-TOPSIS (Maity et al 2013). During the evaluation of the performance rating of alternative, same criteria weights were used as it was used for fuzzy-MARCOS method and the obtained results presented in Fig.…”

Section: Comparison With Other Madm Methodsmentioning

confidence: 99%

Application of integrated BWM Fuzzy-MARCOS approach for coating material selection in tooling industries

Kumar

Maity

Patnaik

2021

Preprint

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The life of metal forming dies, and the efficiency of tooling industries depends on the mechanical and wear properties of tool steel. These properties can be further improved by depositing the ceramic coating on heat-treated tool steel. There are many coating materials available with numerous excellent properties. But problem is how to select the best coating material. Compared to various studies related to material selection problems in the contrasting area of utilization, remarkably, few research work is done in tooling industries. In the present work, we have identified eight coating materials (alternatives) and nine evaluation criteria under the consultation of an expert in the tooling application and tribological field. To deal with this coating material selection problem, an integrated fuzzy-MADM method is proposed comprising BWM and fuzzy-MARCOS. This integrated fuzzy-MADM method is used to evaluate the alternative, and the obtained results are scrutinized under extensive use of sensitivity analysis. In the first phase of analysis, seven scenarios of criteria weight change are used, which is derived by the BWM method; dynamic matrices are used in the second phase of analysis. In the third and fourth phases, obtained ranks are compared with those obtained by different weight calculation methods and ranking methods, respectively. All the phases have similar results, i.e., AlCrN/TiAlN coating (alternative Cm5) is the best coating material. What is more, the proposed method has been used to solve the published results of coating material selection. To evaluate its reliability and robustness, a four phases comparative sensitivity analysis was performed.

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Section: Comparison With Other Madm Methodsmentioning

confidence: 99%

Application of integrated BWM Fuzzy-MARCOS approach for coating material selection in tooling industries

Kumar

Maity

Patnaik

2021

Preprint

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“…Moreover, Alkan and Albayrak [45] aimed to rank renewable energy sources for different regions of Turkey. Within this framework, the criteria are weighted with fuzzy Entropy method.…”

Section: B Mcdm Models In Renewable Energy Investmentsmentioning

confidence: 99%

An Extended Pythagorean Fuzzy Approach to Group Decision-Making With Incomplete Preferences for Analyzing Balanced Scorecard-Based Renewable Energy Investments

et al. 2021

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The aim of this study is to generate appropriate strategies to improve renewable energy investments. Within this framework, a novel model has also been proposed which includes three different stages. Firstly, incomplete preferences of the relation matrixes are calculated. For this purpose, 4 different decision makers evaluate the balanced scorecard-based criteria. In this stage, missing values are estimated by incomplete preferences to complete the relation matrixes. Additionally, the second stage includes the computing the fuzzy preferences by considering the consensus-based group decision-making (CGDM). The final stage is related to the calculation of the weights of the criteria by considering Pythagorean fuzzy decision-making trial and evaluation laboratory (DEMATEL) methodology. Hence, the main motivation of this study is to identify innovative strategies for the renewable energy investments with a novel multicriteria decision-making (MCDM) model based on incomplete preferences, CGDM and Pythagorean fuzzy sets. The findings indicate that learning and growth is the most important balanced scorecard-based perspective to improve the performance of renewable energy investments. Additionally, the perspective of internal process is identified as another significant factor for this situation. The biggest problem in renewable energy projects is their high initial costs. Hence, technological developments reduce the production costs of renewable energy sources. Additionally, it is also possible to increase the amount of electricity from renewable energy sources owing to the innovative technologies. Thus, renewable energy investors should follow up-to-date technological developments so that it will be possible to reduce the cost of renewable energy investments.

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“…The usability of the MOORA method has been demonstrated in numerous cases, such as: credit evaluation model using MOORA method (İç, 2020); evaluation of the work performance (Fadli and Imtihan, 2019); decisionmaking in the production system (Attri and Grover, 2014); supplier selection (Karande and Chakraborty, 2012); decision-making in a manufacturing environment (Chakraborty, 2011); privatization in a transition economy (Brauers and Zavadskas, 2006), and so on. When it comes to the MULTIMOORA method, the same has also been applied in various and numerous cases, such as: personnel selection (Karabasevic et al, 2015;Baležentis et al, 2012); risk assessment (Liu et al, 2014); project management (Brauers and Zavadskas, 2010); strategy assessment (Fedajev et al, 2020); ranking of the renewable energy sources (Alkan and Albayrak, 2020); site selection (Rahimi et al, 2020); hybrid vehicle engine selection (Hafezalkotob et al, 2019b), and so on. Integration of several proven multicriteria approaches for ranking alternatives and the use of dominance theory for the final ranking of alternatives can be mentioned as an important characteristic of these methods, which is also proven in the above-mentioned articles.…”

Section: Introductionmentioning

confidence: 99%

Developing of a Novel Integrated MCDM MULTIMOOSRAL Approach for Supplier Selection

Ulutaş¹,

Stanujkić²,

Karabašević³

et al. 2021

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The main aim of the article is to propose a new multiple criteria decision-making approach for selecting alternatives, the newly-developed MULTIMOOSRAL approach, which integrates advantages of the three well-known and prominent multiple-criteria decision-making methods: MOOSRA, MOORA, and MULTIMOORA. More specifically, the MULTIMOOSRAL method has been further upgraded with an approach that can be clearly seen in the well-known WASPAS and CoCoSo methods, which rely on the integration of weighted sum and weighted product approaches. In addition to the above approaches, the MULTIMOOSRAL method also integrates a logarithmic approximation approach. The expectation from the development of this method is that the integration of several approaches can provide a much more reliable selection of the most appropriate alternative, which can be very important in cases where the performance of alternatives obtained by using some other method does not differ much. Finally, the ranking of alternatives based on the dominance theory, used in the MOORA and MULTIMOORA methods, is replaced by a new original approach that should allow a much simpler final ranking of alternatives in order to reach a stronger result with five different techniques. The suitability and efficacy of the proposed MULTIMOOSRAL approach are presented through an illustrative case study of the supplier selection.

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Ranking of renewable energy sources for regions in Turkey by fuzzy entropy based fuzzy COPRAS and fuzzy MULTIMOORA

Cited by 115 publications

References 68 publications

Application of integrated BWM Fuzzy-MARCOS approach for coating material selection in tooling industries

Application of integrated BWM Fuzzy-MARCOS approach for coating material selection in tooling industries

An Extended Pythagorean Fuzzy Approach to Group Decision-Making With Incomplete Preferences for Analyzing Balanced Scorecard-Based Renewable Energy Investments

Developing of a Novel Integrated MCDM MULTIMOOSRAL Approach for Supplier Selection

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