Search Results (9)

In this study, a combined multi-criteria decision-making (MCDM) approach that integrates the logarithm methodology of additive weights (LMAW) and the double normalization-based multiple aggregation (DNMA) methods has been utilized to determine the optimal fabric structures considering the performance characteristics of denim fabrics containing recycled cotton. This approach focuses on sustainability and performance criteria, applying advanced decision-making methodologies to provide in-depth analysis and guidance for denim fabric selection. In this research, 15 distinct criteria were taken into account. Alternatives were ranked based on outcomes obtained from these methods. Although it was not anticipated that the top-ranked alternatives would simultaneously fulfill the beneficial or non-beneficial orientation of all criteria, an examination of the top three alternatives (A12, A5, and A15) for both garment groups revealed that they indeed aligned with the pre-determined criterion orientation. This highlights the effectiveness of the multi-criteria decision-making approach in the context of this study. Full article

This research investigates the optimal integration of Blockchain Technology (BT) in Supply Chain Management (SCM) within Chile’s maritime ports. Utilizing fuzzy Logarithmic Methodology of Additive Weights (LMAW) and Double Normalization-based Multiple Aggregation Methods (DNMA), the study systematically identifies, prioritizes, and ranks key factors influencing BT adoption in SCM. The study’s findings highlight crucial factors like enhanced transaction security, good supply chain practices, and risk management. Furthermore, it ranks the application of ports as prime candidates for BT integration. The research contributes theoretically by developing a hybrid model combining MCDA methods, and practically by guiding the strategic application of BT in the maritime logistics sector, aligning with the principles of Industry 5.0. This paper presents a novel approach that explores the utilization of BT in maritime supply chain management, incorporating MCDA in a vague environment. The research gap of this study lies in defining new contexts in both theoretical and practical literature reviews for extending the use of BT in SCM in the ports of Chile, according to Industry 5.0, to increase the efficiency and effectiveness of all aspects of operations in these places. The contribution of this research is applying hybrid MCDA methods in an uncertain environment to assist decision-makers (DMs) in better implementing BT in SCM in Chilean ports, according to Industry 5.0. Full article

As technology continues to shape the landscape of education, the need for effective evaluation frameworks for sustainable technology-enhanced learning (TEL) becomes increasingly vital. This study presents an expert-opinion-based evaluation framework, utilizing Z-numbers and the fuzzy logarithm methodology of additive weights (LMAW), to assess the sustainability of TEL approaches. This framework focuses on four main criteria: cloud services compliance, cloud M-Learning essentials, system and technological advancement, and organizations management readiness. Additionally, it incorporates 17 sub-criteria to provide a comprehensive evaluation of the system. Drawing on the expertise of subject matter specialists, the evaluation framework utilizes Z-numbers to account for the inherent uncertainty and imprecision in expert judgments. The fuzzy LMAW is applied to calculate the overall scores for each criterion and sub-criterion, enabling a quantitative measure of their importance in the evaluation process. The findings of this study will contribute to the development of a robust and scientifically rigorous evaluation framework for sustainable TEL. By incorporating expert opinions and employing Z-LMAW, decision-makers and stakeholders can objectively assess the sustainability of TEL systems. This framework holds promise for informing the design and implementation of strategies to enhance the quality, compliance, and technological advancements in TEL environments. Full article

The evolving customer demands have significantly influenced the operational landscape of agricultural companies, including the transformation of their supply chains. As a response, many organizations are increasingly adopting green supply chain practices. This paper focuses on the initial step of selecting a green supplier, using the case study of the Semberka Company. The objective is to align the company with customer requirements and market trends. Expert decision making, grounded in linguistic values, was employed to facilitate the transformation of these values into fuzzy numbers and subsequently derive rough number boundaries. Ten economic-environmental criteria were identified, and six suppliers were evaluated against these criteria. The fuzzy rough LMAW (Logarithm Methodology of Additive Weights) method was employed to determine the criteria weights, with emphasis placed on the quality criterion. The fuzzy rough MABAC (Multi-Attributive Border Approximation Area Comparison) method was then utilized to rank the suppliers and identify the top performer. The validity of the results was established through validation techniques and sensitivity analysis. This research contributes a novel approach to green supplier selection, employing the powerful tool of fuzzy rough sets. The flexible nature of this approach suggests its potential application in future investigations. The limitation of this study is more complicated calculations for the decision maker. However, this approach is adapted to human thinking and minimizes ambiguity and uncertainty in decision making, and in future research, it is necessary to combine this approach with other methods of multi-criteria analysis. Full article

Crop insurance is used to reduce risk in agriculture. This research is focused on selecting an insurance company that provides the best policy conditions for crop insurance. A total of five insurance companies that provide crop insurance services in the Republic of Serbia were selected. To choose the insurance company that provides the best policy conditions for farmers, expert opinions were solicited. In addition, fuzzy methods were used to assess the weights of the various criteria and to evaluate insurance companies. The weight of each criterion was determined using a combined approach based on fuzzy LMAW (the logarithm methodology of additive weights) and entropy methods. Fuzzy LMAW was used to determine the weights subjectively through expert ratings, while fuzzy entropy was used to determine the weights objectively. The results of these methods showed that the price criterion received the highest weight. The selection of the insurance company was made using the fuzzy CRADIS (compromise ranking of alternatives, from distance to ideal solution) method. The results of this method showed that the insurance company DDOR offers the best conditions for crop insurance for farmers. These results were confirmed by a validation of the results and sensitivity analysis. Based on all of this, it was shown that fuzzy methods can be used in the selection of insurance companies. Full article

With the high impetus in global digitization, online shopping (OS) is anticipated to increase further in the near future. Contrary to this anticipation, however, recent studies have emphasized a certain amount of drop in a considerable number of online purchasing transactions in 2022. One of the reasons might be customer dissatisfaction. To analyze online customer reviews, manual sentiment analysis was conducted to detect which quality criteria cause the dissatisfaction of online shoppers. The quality parameters are categorized into product, delivery service, and aftersales service quality (SQ). These main quality criteria are then divided into sub-factors. Eight health category products, including personal care products, wellness products, and household cleaners, were ranked to the importance of the sub-quality parameters using the multi-criteria decision-making (MCDM) method. In this study, a new hybrid MCDM method was also proposed, which combines the triangular fuzzy logarithm methodology of additive weights (F-LMAW) and the Fermatean fuzzy weighted aggregated sum product assessment method (FF-WASPAS). The study reveals that the most important criteria were products’ performance, as well as their side effects, pay-back, and change possibility, while the products’ reasonable price was the least important criterion. Aftersales service was more significant than delivery service. Furthermore, moisturizing creams and medical pillows were the most popular products bought in OS compared with hair conditioners and washing liquids. The study’s multifold contributions and managerial implications were elaborately discussed. Full article

The goal of this research was to find a selection of green suppliers (GSS) that will, in the best way, help agricultural producers to apply green agricultural production using uncertainty in decision making. In order to avoid the possibility of uncertainty in the expert decision making, Z-numbers were used together with the fuzzy LMAW (Logarithm Methodology of Additive Weights) method and fuzzy CRADIS (Compromise Ranking of Alternatives from Distance to Ideal Solution) method. By applying Z-numbers and the fuzzy LMAW method, the weighting coefficients of the criteria were determined, where the experts, in addition to the criteria ratings, also defined the degrees of certainty in the criteria ratings they gave. The obtained results indicated that the criteria related to price and qualities are the most important during the selection process. To select the best alternative, the CRADIS method modified with Z-numbers and fuzzy numbers was applied. The results obtained by applying this method showed that suppliers A2 and A3 have the best characteristics and are the first choice for the procurement of raw and production materials. As part of the paper, the validation of the results and the sensitivity analysis of the model were carried out by conducting the procedure of comparing the obtained results with the results obtained by other MCDM methods and changing the weighting coefficients of the criteria. These analyses indicated that the model presented provides stable results. The conducted research showed how Z-numbers can be used to reduce uncertainty in decision making and how Z-numbers can be used with other fuzzy methods to perform GSS. Full article

The Logarithm Methodology of Additive Weights (LMAW) method is a very young method and in its basic form is defined for crisp values. In this paper, the LMAW method was improved by being modified with triangular fuzzy numbers. The modification significantly improved the capacity of the LMAW method to consider uncertainty in decision making. The special importance of the method is reflected in a relatively simple mathematical apparatus due to which it is possible to define, with high quality, weight coefficients of criteria and rank alternative solutions in uncertain environments. The method was tested in solving the problem of the location selection for a landing operations point (LOP) in combat operations of the army. The validation of the obtained results was performed: (1) by means of comparison with the Fuzzy Simple Additive Weighting (FSAW) Method, the Fuzzy Multi-Attributive Border Approximation area Comparison (FMABAC), the fuzzy Višekriterijumsko KOmpromisno Rangiranje (FVIKOR), the fuzzy COmpressed PRoportional ASsessment (FCOPRAS), and the fuzzy Multi Attributive Ideal-Real Comparative Analysis (FMAIRCA); (2) by means of sensitivity analysis by changing the weight coefficients of criteria; and (3) using simulation software. In comparison with other methods, the quality of the ranking of alternative solutions was confirmed, which highlighted the special importance of the fuzzy LMAW method relative to that of certain standard methods, respectively, the ones that are often used and confirmed in practice. On the other hand, the sensitivity analysis, including the changing of the weight coefficients of criteria, showed that the model could tolerate smaller errors in defining the weight coefficients of criteria, and it provided stable results. Finally, the validation of results achieved with the use of simulation software confirmed the obtained output results. The output results confirmed the quality of the modified method. Full article

Increasing mobility directly affects traffic frequency and thus increases the possible risk of traffic accident occurrences. Taking this into account, it is necessary to create models for determining risk and to act preventively based on these models; this is of great importance both to society and science. In this paper, six measuring sections of a road network are considered on the basis of eight geometric-exploitation road parameters, taking into account the data for light goods vehicles. An original methodology is proposed for identifying risk levels of road sections through their evaluation. For identifying risk levels, the Dombi Logarithmic Methodology of Additive Weights (D’LMAW) was used, which was combined with the Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS) method. Statistical indicators were processed using a hybrid methodology based on the application of rough numbers and Dombi–Bonferroni functions. The performance of the presented methodology was verified on a real-world example, processing the statistical parameters of six two-lane road sections, with the sixth measuring section showing the best performance, since it had the minimum risk. Research has shown that measuring sections with increasing longitudinal gradients are safer. The analysis of measuring sections from fall to rise reduces the deviation of speeds from the speed limit on the roads. The effectiveness, rationality, and robustness of the solution of the proposed methodology was confirmed through a sensitivity analysis. Full article