This paper presents a hybrid multicriteria decision-making (MCDM) model that integrates the fuzzy DIBR II (Defining Interrelationships Between Ranked Criteria II) method with the MABAC (Multi-Attributive Border Approximation Area Comparison). The proposed model addresses the problem of selecting an appropriate flood protection method for Arilje, Republic of Serbia. Flooding in this region results from the overflow of the Veliki Rzav river, which lacks constructed water structures for flood protection. The study considers three alternative flood protection solutions: sand-filled bags, mobile freestanding plastic systems, and mobile freestanding metal systems. The fuzzy DIBR II method was used to define the weighting coefficients of the criteria within a group decision-making framework. Next, the MABAC method was applied to rank the proposed alternatives. Finally, the results were validated through sensitivity analysis and comparative analysis. The validation confirmed that the developed hybrid model produces stable and reliable results.
One of the complex decision-making problems, which requires consideration of several criteria, is the choice of a smartphone. This paper presents an approach that combines user review analysis with machine learning and multi-criteria decision making (MCDM) methods to identify and evaluate alternatives. Based on the processed reviews, the Random Forest algorithm was used to identify the criteria that most influence the selection of smartphones. The weights of the criteria were determined using the Defining Interrelationships Between Ranked criteria II (DIBR II) method, improved by the application of triangular fuzzy numbers for better processing of the subjective and imprecise nature of the data. For the final selection of the optimal alternative, the Weighted Aggregated Sum Product Assessment (WASPAS) method was applied in a fuzzy environment, which enables the combination of additive and multiplicative approaches in ranking. The methodological justification of the proposed approach was confirmed by a sensitivity analysis, through 15 scenarios of changes in the weight coefficients of the criteria, which showed that small oscillations in the weights do not significantly affect the final ranking, especially not in the first two positions. The validation was additionally supported by a comparative analysis with four other decision-making methods in a fuzzy environment, which confirmed the stability and consistency of the results. The proposed approach provides an empirically grounded and methodologically robust framework for solving decision-making problems under conditions of multi-criteria evaluation and uncertainty, and can be applied to a wide range of similar problems in different fields.
Smart technologies are increasingly used in agriculture, with drones becoming one of the key tools in agricultural production. This study aims to evaluate affordable drones for agricultural use in the Posavina region, located in northern Bosnia and Herzegovina. To determine which drones deliver the best results for small and medium-sized farms, ten criteria were used to evaluate eight drones. Through expert evaluation, relevant criteria were first established and then used to assess the drones. The selected drones are designed for crop monitoring and are priced under EUR 2000. Using the fuzzy A-SWARA (Adapted Step-wise Weight Assessment Ratio Analysis) method, it was determined that the most important criteria for drone selection are control precision, flight autonomy, and ease of use, all of which are technical attributes. The fuzzy MARCOS method revealed that the best-performing drones are also the most affordable. The drones D5, D4, and D8 demonstrated the best results. These findings were confirmed through comparative analysis and sensitivity analysis. Their features are not significantly different from those of more expensive models and can, therefore, be effectively used for smart agriculture. This study demonstrates that drones can be a valuable tool for small farms, helping to enhance agricultural practices and productivity.
More and more investments are being made in energy conversion projects from renewable energy sources (RESs), and a large number of investors are entering this sector. The focus of this study is the decision-making by the investor BD Green Energy in the Brčko District of Bosnia and Herzegovina. In order to choose the RES system that would realize this investment in the most efficient way, expert decision-making based on the fuzzy–rough approach and the Bonferroni mean operator was used. Determining the importance of the criteria was conducted using the fuzzy–rough SiWeC (simple weight calculation) method. The results of this method showed that all used criteria have similar importance for the investor. RES system selection was conducted using the fuzzy–rough CoCoSo (combined compromise solution) method. The results of this method showed that investing in photovoltaic (PV) energy is the best for the investor. This research provided guidance on how investors should make investment decisions in RES systems with incomplete information and uncertainty in the decision-making process.
Abstract Energy production, supply and consumption are global issue with many economic, environmental and social implications. Mentioned issue is even more expressed in remote rural areas, in particular in developing countries, as are the countries of the Western Balkans (WB). Renewable energy sources (RES) could represent optimal energy alternative for sustainable performing of agricultural and other activities, as well as for improving the current state of living conditions in rural communities. The main goal of research is to mark the most suitable RES alternative (six alternatives) for wider implementation in rural space of WB. The applied methodology framework implies experts’ opinion (engagement of eight experts) and the use of multi-criteria decision-making methods (MCDM), (specifically fuzzy-rough LMWA and fuzzy-rough CRADIS methods) under the predefined criteria (nine criteria). Derived results show that the implementation of the solar energy plants could play an optimal solution, while as the relatively unsuitable alternative could be marked the use of energy potential of watercourses. Gained final result, i.e. ranking order of the considered alternatives is additionally verified by the appliance of other MCDM methods, while the sensitivity analysis was also performed.
Improving the conditions for the provision of tourist services is critical for the development of tourism. The World Economic Forum uses the Travel and Tourism Development Index (TTDI), calculated based on five main criteria and 17 sub-criteria, to assess these conditions and generate a ranking list of countries based on their favourable environment for conducting tourism-related activities. However, the TTDI only considers the average value of each country's criteria and sub-criteria scores without considering the significance of those criteria. This paper addresses this issue using a hybrid multi-criteria analysis, which combines the MARCOS (Measurement of Alternatives and Ranking According to Compromise Solution) and MEREC (MEthod based on the Removal Effects of Criteria) methods. The results of these methods show that the observed European countries' ranking order differs from the ranking order stated in TTDI. Spain is ranked first, Turkmenistan ranks last, and sensitivity analysis supports these findings. When ranking countries using the TTDI, the importance of the criteria must be considered to accurately reflect the conditions prevailing for tourism development in countries, which is highlighted by this research. This paper's contribution demonstrates that all criteria cannot be considered equally to form the TTDI, as the requirements cannot be equally important.
With the development of agricultural production, the demand for electricity correspondingly increases. To sustainably meet this demand, renewable energy sources (RESs) can be utilized. This paper explores the application of RES alternatives in agriculture to provide guidelines for enhancing sustainable agricultural practices in Bosnia and Herzegovina. The study employs expert decision making using fuzzy multi-criteria decision-making (MCDM) methods. A decision-making model incorporating nine criteria and six alternatives was developed. Using the direct weight calculation (DiWeC) approach, the findings indicate that economic criteria are prioritized over other sustainability criteria. The results from the fuzzy RAWEC (ranking of alternatives with weights of criteria) method reveal that solar energy has the greatest potential for advancing sustainable agricultural production in Bosnia and Herzegovina. For practical implementation of RES alternatives, active involvement from state institutions and local communities is essential.
This paper presents a multi-criteria decision-making model based on the application of two methods, DIBR II and MABAC. The DIBR II method was used to define weight coefficients. The MABAC method was used to rank alternatives, and it was applied in a rough environment. Four experts were engaged in defining the criteria and alternatives as well as in the relation of criteria. The model was applied for ranking the methods and techniques of Lean organization systems management in the maintenance of technical systems of special purposes. At the end of the application was conducted a sensitivity analysis which proved the stability of the obtained results.
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