The main goal of this paper is to propose a Multiple-Criteria Decision-Making (MCDM) approach that will facilitate decision-making in the field of logistics—i.e., in the selection of the optimal equipment for performing a logistics activity. For defining the objective weights of the criteria, the correlation coefficient and the standard deviation (CCSD method) are applied. Furthermore, for determining the semi-objective weights of the considered criteria, the indifference threshold-based attribute ratio analysis method (ITARA) is used. In this way, by combining these two methods, the weights of the criteria are determined with a higher degree of reliability. For the final ranking of the alternatives, the measurement of alternatives and ranking according to the compromise solution method (MARCOS) is utilized. For demonstrating the applicability of the proposed approach, an illustrative case study pointing to the selection of the best manual stacker for a small warehouse is performed. The final results are compared with the ones obtained using the other proved MCDM methods that confirmed the reliability and stability of the proposed approach. The proposed integrated approach shows itself as a suitable technique for applying in the process of logistics equipment selection, because it defines the most influential criteria and the optimal choice with regard to all of them in a relatively easy and comprehensive way. Additionally, conceiving the determination of the criteria with the combination of objective and semi-objective methods enables defining the objective weights concerning the attitudes of the involved decision-makers, which finally leads to more reliable results.
The development of information and communication technologies has revolutionized and changed the way we do business in various areas. The field of education did not remain immune to the mentioned changes; there was a gradual integration of the educational process and the mentioned technologies. As a result, platforms for distance learning, as well as the organization of e-learning courses of various types, have been developed. The rapid development of e-learning courses has led to the problem of e-learning course selection and evaluation. The problem of the e-learning course selection can be successfully solved by using multiple-criteria decision-making (MCDM) methods. Therefore, the aim of the paper is to propose an integrated approach based on the MCDM methods and symmetry principles for e-learning course selection. The pivot pairwise relative criteria importance assessment (PIPRECIA) method is used for determining the weights of criteria, and the interval-valued triangular fuzzy additive ratio assessment (ARAS) method is used for the ranking of alternatives i.e., e-learning courses. The suitability of the proposed integrated model is demonstrated through a numerical case study.
Investment projects can have a significant impact on the functioning and development of a company. Therefore, the selection of one or more investment projects from the set of possible is an important and difficult task for decision makers. This paper considers the investment projects selection based on financial analysis criteria and use of imprecise data. In the proposed model, the alternative projects performances are expressed using crisp and interval values, and then the best project from the available is selected by using COPRAS and COPRAS-G methods. A numerical example is given to demonstrate the applicability and effectiveness of the proposed approach.
The United Nations Member States adopted the “Agenda 2030” which contains 17 sustainable development goals (SDG) that involve a certain number of targets and indicators. Although the indicators are helpful in defining the position of the current country relative to the goals’ achievement, it is very complex to determine its position relative to other countries, because this requires an extensive analysis. Therefore, in this paper, the application of the multiple-criteria decision-making approach (MCDM) in defining the position of the EU (Europe Union) countries relative to the SDGs is proposed. The MCDM model is based on the Combined Compromise Solution (CoCoSo) and the Shannon Entropy methods. The final results highlight Sweden as the country that best implemented the set SD goals and has the best outputs relative to them, while Romania is in last place. The main reason for these kinds of results could be that the countries on the bottom of the list are relatively new EU members and have not been made to properly implement SDGs yet. The conclusion is that the obtained results are fully objective and rational, and that the applied model is applicable for performing this kind of analysis.
Neutrosophic sets have been recognized as an effective approach in solving complex decision-making (DM) problems, mainly when such problems are related to uncertainties, as published in numerous articles thus far. The use of the three membership functions that can be used to express accuracy, inaccuracy, and indeterminacy during the evaluation of alternatives in multiple-criteria DM can be said to be a significant advantage of these sets. By utilizing these membership functions, neutrosophic sets provide an efficient and flexible approach to the evaluation of alternatives, even if DM problems are related to uncertainty and predictions. On the other hand, the TOPSIS method is a prominent multiple-criteria decision-making method used so far to solve numerous decision-making problems, and many extensions of the TOPSIS method are proposed to enable the use of different types of fuzzy as well as neutrosophic sets. Therefore, a novel extension of the TOPSIS method adapted for the use of single-valued neutrosophic sets was considered in this paper.
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