• Proceedings of the Korea Contents Association Conference
• /
• 2014.11a
• /
• pp.469-470
• /
• 2014

동적 무기할당 문제는 전형적인 NP-완전 문제로써 위협하는 표적에 대해 아군의 무기를 적절히 할당하는 문제이다. 이는 매우 시간 제약적인 문제로써 가능한 단 시간 내에 적절한 무기할당 및 대응을 도출하여야 하지만 매우 유동적인 전장 환경에서 이는 쉽지 않다. 최근 이와 같이 높은 복잡성을 가진 빅데이터를 기반으로 하는 응용에서 분산 처리 시스템을 활용한 분석 및 처리에 대한 연구가 큰 주목을 받고 있고, 대표적인 프레임워크로써 맵리듀스가 활용되고 있다. 그러나 맵리듀스는 전체 데이터에 대한 일괄 처리 기능만을 제공하므로 동적 데이터에 대한 유전자 알고리즘의 수행이 쉽지 않고, 최종 결과 도출에 여전히 많은 시간을 필요로 한다. 본 논문에서는 맵리듀스 환경에서 유전자 알고리즘 기반의 동적 무기할당 알고리즘을 제안한다. 제안하는 기법에서는 맵리듀스 환경에서 유전자 알고리즘의 연속적인 데이터 처리의 지원을 위해 새롭게 추가 및 제거된 무기-표적 데이터만을 분석하고, 이를 기 분석 완료된 데이터와 결합하여 최종 결과를 도출한다. 이를 통해, 신속한 동적무기할당의 수행이 가능하다.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.50 no.4
• /
• pp.287-295
• /
• 2022

As low altitude long-range artillery threat has been strengthened, the development of anti-artillery interception system to protect assets against its attacks will be kicked off. We view the defense of long-range artillery attacks as a typical dynamic weapon target assignment (DWTA) problem. DWTA is a sequential decision process in which decision making under future uncertain attacks affects the subsequent decision processes and its results. These are typical characteristics of Markov decision process (MDP) model. We formulate the problem as a MDP model to examine the assignment policy for the defender. The proximity of the capital of South Korea to North Korea border limits the computation time for its solution to a few second. Within the allowed time interval, it is impossible to compute the exact optimal solution. We apply approximate dynamic programming (ADP) approach to check if ADP approach solve the MDP model within processing time limit. We employ Shoot-Shoot-Look policy as a baseline strategy and compare it with ADP approach for three scenarios. Simulation results show that ADP approach provide better solution than the baseline strategy.

• Journal of the Korea Society for Simulation
• /
• v.27 no.2
• /
• pp.35-48
• /
• 2018

The study of air defense against North Korean tactical ballistic missiles (TBM) should consider the rapidly changing battlefield environment. The study for target re-designation for intercept missiles enables effective operation of friendly defensive assets as well as responses to dynamic battlefield. The researches that have been conducted so far do not represent real-time dynamic battlefield situation because the hit probability for the TBM, which plays an important role in the decision making process, is fixed. Therefore, this study proposes a target re-designation algorithm that makes decision based on hit probability which considers real-time field environment. The proposed method contains a trajectory prediction model that predicts the expected trajectory of the TBM from the current position and velocity information by using random forest and moving window. The predicted hit probability can be calculated through the trajectory prediction model and the simulator of the intercept missile, and the calculated hit probability becomes the decision criterion of the target re-designation algorithm for the missile. In the experiment, the validity of the methodology used in the TBM trajectory prediction model was verified and the superiority of using the hit probability through the proposed model in the target re-designation decision making process was validated.