► The fuzzy MULTIMOORA method was extended to tackle group decision making. ► The fuzzy weighted averaging (FWA) operator was applied for aggregation. ► The case of personnel selection based on ...linguistic variables is presented.
Personnel selection process is aimed at choosing the best candidate to fill the defined vacancy in a company. It determines the input quality of personnel and thus plays an important role in human resource management. Given the uncertain, ambiguous, and vague nature of personnel selection process, it requires the application of multi-criteria decision making (MCDM) methods for robust recruitment. This paper hence is aimed at extending the fuzzy MULTIMOORA for linguistic reasoning under group decision making. The fuzzy MULTIMOORA was further modified in this study. The fuzzy MULTIMOORA for group decision making (MULTIMOORA–FG) enables to aggregate subjective assessments of the decision-makers and thus offer an opportunity to perform more robust personnel selection procedures. A personnel selection problem illustrated the group decision-making procedure according to MULTIMOORA–FG: the enterprise has formed an executive committee consisting of four decision-makers to choose the best candidate from another four participants to fill the vacancy. The committee has decided to consider eight qualitative attributes expressed in linguistic variables. The numerical example exhibited possibilities for improvement of human resources management as well as any other business decision area by applying MULTIMOORA–FG.
The aim of this manuscript is to propose a new extension of the MULTIMOORA method adapted for usage with a neutrosophic set. By using single valued neutrosophic sets, the MULTIMOORA method can be ...more efficient for solving complex problems whose solving requires assessment and prediction, i.e. those problems associated with inaccurate and unreliable data. The suitability of the proposed approach is presented through an example.
The first systematic research on Location Theory dates back to 1826. Quantitative approaches came much later. On the supply side extensive Input-Output Tables can be mentioned and on the demand side ...the optimization by Multi-Criteria Decision Making. The advantages of Input-Output Tables for location opportunities on a regional and urban basis have to be emphasized, whereas the link is made between Input-Output and Multi-Criteria Optimization. MOORA, Multi-Objective Optimization by Ratio Analysis, is composed of two methods: Ratio Analysis and Reference Point Theory and responds to the different conditions of robustness needed for optimization. This approach attempts to localize in an optimal way a certain project facing different indicators, criteria or objectives sometimes originating from different groups or individuals. Here however type and importance of objectives and alternatives were only simulated. The real stakeholders to be considered are rather the national and local authorities, the contributing firms and their personnel. In the production sphere consumer sovereignty was only indirectly involved. If consumers, via consumer organizations and trade unions, were directly involved, other claims could emerge. The simulation used was limited in its applications. Clearly if this simulation has no practical consequences, it still provides a learning experience with the use of the MOORA Method in its double composition.
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.
Credit Rating Agencies rate firms and countries by internal experts but with a final qualitative judgment by their management acting as decision makers. These ratings on their turn influence the ...countries credit rating and ipso facto of their enterprises. The work of the CRA is in fact double: credit rating of firms and other organizations at one side and countries on the other. Considering the credit rating of firms, the CRA made significant mistakes during the Recession 2007−2009 and their judgment is too much American oriented, in any way from a European point of view. Consequently, in Europe many efforts were made to come to a new agency, but all efforts failed. It could be different for the rating of countries. Is a more scientific approach, eventually on a quantitative and structural basis, not possible? Therefore, MULTIMOORA, a quantitative method, is suggested. The study was made for all countries of the European Continent. Based on data available in 2013 and on their extrapolation, the results are quite comparable to the results of Standard & Poor’s Credit Rating System of the moment. As the classifications of Moody’s and Fitch are very similar to those of Standard & Poor’s the outcome would be similar for these other Credit Rating Agencies.
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•We suggest a hybrid MCDM approach considering big data structure.•CLUS-MCDA: cluster analysis for improving Multiple Criteria Decision Analysis.•CLUS-MCDA method is combination of ...k-means technique and MULTIMOORA method.•We present an example concerning the supplier selection problem.•The input data of the case-study is big data structured.
In past recent years, by increasing in the considerations on the significance of data science many studies have been developed concerning the big data structured problems. Along with the information science, in the field of decision science, multi-attribute decision-making (MADM) approaches have been considerably applied in research studies. One of the most important procedures in supply chain management is selecting the optimal supplier to maintain the long-term productivity of the supply chain. There has been a vast amount of research which utilized MADM approaches to tackle the supplier selection problems, but only a few of these research considered big data structured problems. The current study presents a comprehensive novel approach for improving Multiple Criteria Decision Analysis (MCDA) based on cluster analysis considering crisp big data structure input which is called CLUS-MCDA (Cluster analysis for improving Multiple Criteria Decision Analysis) algorithm. The proposed method is based on consolidating a data mining technique i.e. k-means clustering method and a MADM approach which is MULTIMOORA method. CLUS-MCDA method is a fast and practical approach which has been developed in this research which is implied in a supplier selection problem considering crisp big data structured input. A real-world case study in MAMUT multi-national corporation has been presented to show the validity and practicality of the CLUS-MCDA approach which calculated considering the business areas and criteria based on expert comments of mentioned organizations and previous literature on supplier selection problem.
Many real-world decision-making problems are complex and placed in a fuzzy environment, especially when it is related to predictions and assessments. Therefore, an extension of the MULTIMOORA method, ...primarily adapted for the use of interval-valued triangular fuzzy numbers as well as the use of the group decision-making approach and linguistic variables, is proposed in this paper. In order to demonstrate the applicability and effectiveness of the proposed approach, an example of comminution circuits design selection is considered. web URL: http://www.transformations.khf.vu.lt/35b/article/anex
Through the implementation of the “Europe 2020” strategy, the European Union (EU) strives to ensure sustainable growth and development by 2020, improve its competitive position in the global market ...and become one of the most dynamic knowledge-based economies worldwide. Having in mind the fact that the year 2020 is approaching, some important questions arising and need to be addressed. Which Member States are the best and which are the worst performers in the implementation of the “Europe 2020” strategy? How can they be classified according to the progress they have made in the strategy implementation? In which strategic priorities is the gap amongst Member States high and in which is the state relatively uniform?
In order to address these questions, a multi-objective decision-making approach is used for the ranking and classification of the EU countries according to the progress achieved in the implementation of the strategy. The weights of the considered criteria are calculated objectively by applying the entropy method. The entropy method is also used for the calculation of the Shannon Entropy Index, which measures the inequality in the performances of the Member States in each strategic priority. The obtained results pointed out the Sweden, Denmark and Austria are the best performers in strategy implementation. Among EU-15, Finland and France were also positioned relatively high in the rankings. On the other hand, some new Member States achieved significant progress in the strategy implementation and over performed some old Member States, like Lithuania, Slovenia, Croatia and Czech Republic, so they joined group of Core countries. In contrast to them, Belgium, Bulgaria, Spain, Italy, Cyprus, Luxembourg, Malta, the Netherlands, and Romania have an unfavorable position in the final ranking, for which reason they are classified into the group of the Peripheral countries. So, these countries should make considerable effort in the future to achieve their national targets in most of strategy priorities and contribute to full implementation of the strategy at the EU level.
Regarding the progress in strategic priorities, the values of the Shannon Entropy Index indicated that relatively higher differences among the EU countries still exist in the development of renewable energy production and investments in research and development (R&D). These priorities are very important for achieving smart and sustainable growth and reducing the gap among Member States in mentioned priorities require, before all, higher investments. So, some additional funds should be allocated for these purposes to countries which significantly lagging behind in reaching their national targets in these priorities.
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•The MULTIMOORA method was applied for ranking and classification.•The Shannon Entropy Index indicate the gap among EU countries in each strategy area.•Sweden, Denmark and Austria are the best performers in strategy implementation.•Malta, the Netherlands, and Romania are positioned at the very end in the rankings.•The gaps in development of renewable energy production are the highest.
Different multiple objectives expressed in different units make optimization difficult. Therefore, the internal mechanical solution of a Ratio System, producing dimensionless numbers, is preferred to ...weights, which are most of the time used to compare the different units. In addition, the ratio system creates the opportunity to use a second approach: a non-subjective Reference Point Theory. Therefore, the Reference Point Theory uses the ratios found in the ratio system as co-ordinates for the alternative solutions, which are then compared to a Maximal Objective Reference Point. The two approaches form a control on each other. This overall theory is called MOORA (Multi-Objective Optimization by Ratio Analysis). The results are still more convincing if a Full Multiplicative Form is added, three methods assembled under the name of MULTIMOORA. At that moment, the control by three different approaches forms a guaranty for a solution being as non-subjective as possible. As to calculate the sum of three obtained ranks is not allowed, a theory of Ordinal Dominance is developed in order to remain in the ordinal sphere.
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