The paper demonstrates a model whose goal is to define the construction elements of weapons necessary to meet minimum requirements of users. The complexity of the problem, conditioned by different construction elements of weapons and specific situations of their use, is the reason for using methods of multi-criteria decision-making. In the paper we used the hybrid LBWA – IR-MAIRCA model. With this model, one can conduct an analysis of characteristics of the existing weapons, based on which we define the construction elements for modifying the existing and manufacturing new weapons. Regarding a large number of different types of weapons, the paper is limited to the analysis of close-quarters combat weapons. The LBWA method was used to calculate weight coefficients of the criteria. The MAIRCA method, which was modified by interval rough numbers, was used to select the best close-quarters combat weapon that has the best characteristics in accordance with the requests of the users. Based on the analysis, the users have the option to clearly and precisely define requests for improvement of the existing, and manufacturing new weapons.

This study considers the problem of selecting an anti-tank missile system (ATMS). The mentioned problem is solved by applying a hybrid multi-criteria decision-making model (MCDM) based on two methods: the DIBR (Defining Interrelationships Between Ranked criteria) and the MABAC (Multi-Attributive Border Approximation area Comparison) methods. The methods are modified by applying rough numbers, which present a very suitable area for considering uncertainty following decision-making processes. The DIBR method is a young method with a simple mathematical apparatus which is based on defining the relation between ranked criteria, that is, adjacent criteria, reducing the number of comparisons. This method defines weight coefficients of criteria, based on the opinion of experts. The MABAC method is used to select the best alternative from the set of the offered ones, based on the distance of the criteria function of every observed alternative from the border approximate area. The paper has two main innovations. With the presented decision-making support model, the ATMS selection problem is raised to a higher level, which is based on a proven mathematical apparatus. In terms of methodology, the main innovation is successful application of the rough DIBR method, which has not been treated in this way in the literature so far. Additionally, an analysis of the literature related to the research problem as well as to the methods used is carried out. After the application of the model, the sensitivity analysis of the output results of the presented model to the change of the weight coefficients of criteria is performed, as well as the comparison of the results of the presented model with other methods. Finally, the proposed model is concluded to be stable and multi-criteria decision-making methods can be a reliable tool to help decision makers in the selection process. The presented model has the potential of being applied in other case studies as it has proven to be a good means for considering uncertainty.

The selection of unmanned aerial vehicles for different purposes is a frequent topic of research. This paper presents a hybrid model of an unmanned aerial vehicle (UAV) selection using the Defining Interrelationships Between Ranked criteria (DIBR), Full Consistency Method (FUCOM), Logarithm Methodology of Additive Weights (LMAW) and grey - Evaluation based on Distance from Average Solution (G-EDAS) methods. The above-mentioned model is tested and confirmed in a case study. First of all, in the paper are defined the criteria conditioning the selection, and then with the help of experts and by applying the DIBR, FUCOM and LMAW methods, the weight coefficients of the criteria are determined. The final values of the weight coefficients are obtained by aggregating the values of the criteria weights from all the three methods using the Bonferroni aggregator. Ranking and selection of the optimal UAV from twenty-three defined alternatives is carried out using the G-EDAS method. Sensitivity analysis confirmed a high degree of consistency of the solutions obtained using other MCDM methods, as well as changing the criteria weight coefficients. The proposed model has proved to be stable; its application is also possible in other areas and it is a reliable tool for decision-makers during the selection process.

This study introduces a hybrid multi-criteria decision-making (MCDM) model combining Spherical Fuzzy AHP and Grey MARCOS methods to evaluate university professors comprehensively. Addressing the limitations of traditional assessment methods, the model incorporates subjective and imprecise data while maintaining transparency and precision. Seven criteria, including teaching quality, accessibility to students, professional competence, preparation and organization, student feedback, contribution to the university, and ethical behavior, were used. Spherical Fuzzy AHP was employed to determine the weight coefficients of the criteria, leveraging fuzzy logic to capture uncertainties. Subsequently, Grey MARCOS ranked professors by evaluating their performance against ideal and anti-ideal solutions using interval grey numbers. The hybrid approach effectively mitigates bias and provides an accurate ranking of alternatives, even under conditions of incomplete or subjective data. The results validate the model's robustness and adaptability, highlighting its utility for both individual evaluations and broader institutional improvements. This methodology offers actionable insights for enhancing teaching quality, encouraging professional growth, and strengthening institutional competitiveness. The findings emphasize the importance of integrating advanced MCDM techniques to ensure comprehensive and equitable assessments in academia. This study provides a practical framework for universities aiming to elevate educational standards while addressing global challenges in higher education evaluation. By applying this hybrid model, institutions can foster a culture of continuous improvement and achieve more reliable and impactful outcomes in professor evaluations.

The paper addresses the selection of the most favorable alternative in the form of assault rifles to meet the requirements arising from modern combat operations. The complexity of the problem, conditioned by the different structural elements of automatic rifles and the specific situations of their use, has caused the application of Multi-Criteria Decision-making (MCDM) methods. A hybrid model was developed to guide the selection of the appropriate automatic rifle. The criteria were defined by experts, where the calculation of the weight coefficients of criteria was performed using the LMAW method Employing the grey EDAS method for MCDM, the study identifies an assault rifle that offers the most advantageous capabilities for carrying out firing tasks in the context of daily combat operations, with the aim of equipping the armed forces and raising the operational capability of the units. The validity of this model was verified through sensitivity analysis involving the adjustment of criteria weight coefficients.

In the pivotal task of selecting an assault boat conducive for military operations, especially amidst the challenges posed by water obstacles, the utilisation of Multi-Criteria Decision-Making (MCDM) methods surfaces as vital. In this investigation, a meticulous application of the DIBR II (Defining Interrelationships Between Ranked criteria II) - BM (Bonfferoni Mean) – CoCoSo (COmbined COmpromise SOlution) multi-criteria decision-making model is performed. Initially, the weight coefficients of the criteria were determined via the DIBR II method, with expert opinions being cohesively aggregated using BM operators. Subsequently, the CoCoSo method was employed to discern the optimal alternative among various assault boats. A comprehensive analysis, entailing the examination of the sensitivity of the output results to alterations in the weight coefficients of the criteria, was conducted post-final ranking of alternatives. Noteworthy is the finding that negligible deviations in defining the weight coefficients by experts do not impose a significant impact on the ultimate selection of the optimal alternative. Furthermore, a comparative analysis alongside other MCDM methods corroborated not only the efficacy but also the superiority of the implemented model. The insights derived underscore the practical applicability, stability, and accuracy of the proposed model in choosing assault boats for military operations. This exploration fortifies the decision-making process in military contexts related to overcoming water obstacles and portends potential applicability in domains necessitating intricate multi-criteria decision-making.