Optimization of Anti-Drone Defense: Analyzing Non-Kinetic Gun Selection Using DIBR II-Grey MARCOS Methodology

The selection of appropriate anti-drone systems is critical for enhancing a military's defensive capabilities. With a range of non-kinetic anti-drone guns available, it is essential to identify the optimal system that meets specific military requirements. This study presents a comprehensive approach, combining Multiple Criteria Decision Making (MCDM) techniques to facilitate this selection process. The Defining Interrelationships Between Ranked Criteria II (DIBR II) method has been employed to determine and calculate the criteria weighting coefficients, while the Grey Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method, modified to utilize interval grey numbers, has been applied to rank the alternatives. The criteria weighting coefficients, defined by expert input, are aggregated using the Bonferroni mean. The proposed DIBR II-Grey MARCOS model is then subjected to a sensitivity analysis, which further validates the robustness of the selection process. A comparative analysis of results, based on the applied MCDM methods, underscores the efficacy of the proposed model. The findings demonstrate that this integrated model not only provides a reliable framework for selecting anti-drone guns but also offers a versatile tool for resolving other MCDM challenges across various domains. The study highlights the potential of this model for broader application in diverse operational environments, where complex decision-making is required. The combination of MCDM techniques and sensitivity analysis offers valuable insights into optimizing resource allocation, thereby enhancing strategic decision-making processes. The proposed model's adaptability and effectiveness suggest its significant potential for adoption beyond the military sector.