Airpower plays a key role in neutralizing military threats and securing victory in wars. This study analyzes newly introduced fighter forces by considering factors like performance, power index, operational environment, airbase capacity, survivability, and sustainment capability to devise an optimal deployment strategy that enhances operational efficiency and effectiveness. Using optimization methods like mixed integer programming (MIP), the study incorporates constraints such as survivability and mission criticality. The focus is on major Air Force operations, including air interdiction, defensive counter-air, close air support, and maritime operations. Experimental results show the proposed model outperforms current deployment plans in both wartime and peacetime in terms of operations and sustainment.

North Korea has repeatedly provoked using unmanned aerial vehicles (UAVs), and the threat posed by UAVs continues to escalate, as evidenced by recent directives involving the use of waste-laden balloons and the development of suicide drones. North Korea’s small UAVs are difficult to detect due to their low radar cross-section (RCS) values, necessitating the efficient deployment and operation of assets for effective response. Against this backdrop, this study aims to predict the infiltration routes of enemy UAVs by considering their perspective, avoiding key facilities and obstacles, and propose deployment strategies to enable rapid detection and response during provocations. Utilizing the Markov Decision Process (MDP) based on previous studies, this research presents a model that reflects both UAV flight characteristics and regional environments. Unlike previous models that designate a single starting point, this study addresses the practical challenge of uncertainty in initial infiltration points by incorporating multiple starting points into the scenarios. By aggregating and integrating the probability maps derived from these variations into a unified map, the model predicts areas with a high likelihood of UAV infiltration over time. Furthermore, based on case studies in the capital region, this research proposes deployment strategies tailored to the specifications of currently known anti-drone integrated systems. These strategies are expected to support military decision-making by enabling the efficient operation of assets in areas with a high probability of UAV infiltration.

This study proposes a mathematical model to optimize the fighter aircraft-weapon combinations for the Republic of Korea Air Force. With the recent emergence of the population cliff issue due to declining birth rates in Korea, there is an urgent need for efficient weapon system operations in light of decreasing military personnel. This study aims to enhance operational environments and mission efficiency within the military. The objective is to reduce the workload of pilots and maintenance personnel by operating an optimal number of weapons instead of deploying all possible armaments for each aircraft type. To achieve this, various factors for optimizing the fighter-weapon combinations were identified and quantified. A model was then constructed using goal programming, with the objective functions based on the compatibility, Circular Error Probable (CEP), and fire range of the weapons, along with the planned wartime mission-specific weapon ratios for each aircraft type. Experimental analysis of the proposed model indicated a significant increase in mission performance efficiency compared to the existing system in both operational and maintenance aspects. It is hoped that this model will be applied in military settings.

This study presents an optimization model for the Tactical Information Communication Network (TICN), which is crucial for military operations, focusing on the efficient deployment of communication nodes to create a rapid and robust network while minimizing both distances and the number of nodes required. By integrating mixed integer programming (MIP) with minimum spanning tree (MST) and Steiner Tree algorithms, the model ensures that nodes are connected through the shortest, most efficient routes. Simulations demonstrate the model’s ability to form cohesive networks under constrained resources and time, reducing transmission distances and maintaining network stability. Case studies in a grid environment confirm the system's efficiency, with the model able to redeploy nodes if damaged to preserve network integrity. By utilizing both high- and low-capacity transmission systems, the model ensures reliable communication in challenging terrains like Korea’s mountainous landscape. The findings have critical implications for military communication strategies, especially for multi-domain operations involving air, land, and sea forces, and support decision-making for rapid and efficient deployment of communication networks in unpredictable conditions.