This study proposes a mathematical model to optimize the fighter aircraft-weapon combinations for the ROKAF(Republic Of Korea Air Force). With the recent emergence of the population declining issue in Republic of Korea, there is an urgent need for efficient weapon system operations in light of decreasing military personnel. In order to solve these issues, we consider 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, CEP(Circular Error Probable), and fire range of the weapons, along with the planned wartime mission-specific weapon ratios for each aircraft type. The experimental result's analysis of the proposed model indicate a significant increase in mission performance efficiency compared to the existing system in both operational and maintenance aspects. We hope that our model will be reflected to help improve the operational capabilities of Republic of Korea Air Force.
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.
Airpower is a crucial force for suppressing military threats and achieving victory in wars. This study evaluates newly introduced fighter forces, considering factors such as fighter performance and power index, operational environment, capacity of each airbase, survivability, and force sustainment capability to determine the optimal deployment plan that maximizes operational effectiveness and efficiency. Research methods include optimization techniques such as MIP(mixed integer programming), allocation problems, and experimental design. This optimal allocation mathematical model is constructed based on various constraints such as survivability, mission criticality, and aircraft's performance data. The scope of the study focuses the fighter force and their operational radius is limited to major Air Force and joint operations, such as air interdiction, defensive counter-air operations, close air support, maritime operations and so on. This study aims to maximize the operational efficiency and effectiveness of fighter aircraft operations. The results of proposed model through experiments showed that it was for superior to the existing deployment plan in terms of operation and sustainment aspects when considering both wartime and peacetime.
As the number of enlistees decreases due to social changes like declining birth rates, it is necessary to conduct research on the appropriate recalculation of the force that considers the future defense sufficiency and sustainability of the Army. However, existing research has primarily focused on qualitative studies based on comprehensive evaluations and expert opinions, lacking consideration of sustained support activities. Due to these limitations, there is a high possibility of differing opinions depending on perspectives and changes over time. In this study, we propose a quantitative method to calculate the proper personnel by applying system dynamics. For this purpose, we consider a standing army that can ensure the sufficiency of defense between battles over time as an adequate force and use battle damage calculated by wargame simulation as input data. The output data is the number of troops required to support activities, taking into account maintenance time, complexity, and difficulty. This study is the first quantitative attempt to calculate the appropriate standing army to keep the defense sufficiency of the ROK Army in 2040, and it is expected to serve as a cornerstone for adding logical and rational diversity to the qualitative force calculation studies that have been conducted so far.
During wartime, the operation of engineering equipment plays a pivotal role in bolstering the combat prowess of military units. To fully harness this combat potential, it is imperative to provide efficient support precisely when and where it is needed most. While previous research has predominantly focused on optimizing equipment combinations to expedite individual mission performance, our model considers routing challenges encompassing multiple missions and temporal constraints. We implement a comprehensive analysis of potential wartime missions and developed a routing model for the operation of engineering equipment that takes into account multiple missions and their respective time windows of required start and completion time. Our approach focused on two primary objectives: maximizing overall capability and minimizing mission duration, all while adhering to a diverse set of constraints, including mission requirements, equipment availability, geographical locations, and time constraints.
In contemporary global warfare, the significance and imperative of air transportation have been steadily growing. The Republic of Korea Air Force currently operates only light and medium-sized military cargo planes, but does not have a heavy one. The current air transportation capability is limited to meet various present and future air transport needs due to lack of performance such as payload, range, cruise speed and altitude. The problem of population cliffs and lack of airplane parking space must also be addressed. These problems can be solved through the introduction of heavy cargo planes. Until now, most studies on the need of heavy cargo plane and increasing air transport capability have focused on the necessity. Some of them suggested specific quantity and model but have not provided scientific evidence. In this study, the appropriate ratio of heavy cargo plane suitable for the Korea's national power was calculated using principal component analysis and cluster analysis. In addition, an optimization model was established to maximize air transport capability considering realistic constraints. Finally we analyze the results of optimization model and compare two alternatives for force structure.
In contemporary global warfare, the significance and imperative of air transportation have been steadily growing. Nevertheless, the Korean Air Force currently operates only with small and medium-sized military cargo planes, lacking larger aircraft. Consequently, the efficiency of their operations is constrained by the limited air transport capacity and the aging of their existing fleet, among other factors. Therefore, we have to consider to make future air transportation capability. Although the 2nd large-sized cargo-plane acquisition project is ongoing, its quantity is very small. In this study, we propose an optimal prediction model that takes into account practical constraints such as parking space availability, pilot availability, wartime daily maximum loads, while simultaneously maximizing both the effectiveness and efficiency of transport capacity for future warfare envirionment.
Amphibious operations represent a pivotal military maneuver involving the transfer of landing forces via ships, boats, and aircraft from sea to land. The success of such operations can be the decisive factor in the outcome of a war. Nevertheless, planning an amphibious assault is an intricate and formidable task, demanding careful consideration of numerous variables. This complexity is particularly evident in the formulation of loading plans for troops and equipment onto naval vessels. Historical accounts underscore the profound repercussions of errors in planning and loading on the execution of these operations. In pursuit of efficient loading procedures characterized by precision and time-effectiveness, our study has delved into the realm of optimization modeling. Employing a mixed-integer mathematical programming approach, this optimization model offers a valuable tool to streamline and enhance the preparatory phase of amphibious operations.
During wartime, the operation of engineering equipment plays a pivotal role in bolstering the combat prowess of military units. To fully harness this combat potential, it is imperative to provide efficient support precisely when and where it is needed most. While previous research has predominantly focused on optimizing equipment combinations to expedite individual mission performance, our model considers routing challenges encompassing multiple missions and temporal constraints. We implement a comprehensive analysis of potential wartime missions and developed a routing model for the operation of engineering equipment that takes into account multiple missions and their respective time windows. Our approach centered on two primary objectives: maximizing overall capability and minimizing mission duration, all while adhering to a diverse set of constraints, including mission requirements, equipment availability, geographical locations, and time constraints.