• Title/Summary/Keyword: Dynamic Weapon Target Assignment

Search Result 5, Processing Time 0.019 seconds

GRASP Algorithm for Dynamic Weapon-Target Assignment Problem (동적 무장할당 문제에서의 GRASP 알고리즘 연구)

  • Park, Kuk-Kwon;Kang, Tae Young;Ryoo, Chang-Kyung;Jung, YoungRan
    • Journal of the Korean Society for Aeronautical & Space Sciences
    • /
    • v.47 no.12
    • /
    • pp.856-864
    • /
    • 2019
  • The weapon-target assignment (WTA) problem is a matter of effectively allocating weapons to a number of threats. The WTA in a rapidly changing dynamic environment of engagement must take into account both of properties of the threat and the weapon and the effect of the previous decision. We propose a method of applying the Greedy Randomized Adaptive Search Procedure (GRASP) algorithm, a kind of meta-heuristic method, to derive optimal solution for a dynamic WTA problem. Firstly, we define a dynamic WTA problem and formulate a mathematical model for applying the algorithm. For the purpose of the assignment strategy, the objective function is defined and time-varying constraints are considered. The dynamic WTA problem is then solved by applying the GRASP algorithm. The optimal solution characteristics of the formalized dynamic WTA problem are analyzed through the simulation, and the algorithm performance is verified via the Monte-Carlo simulation.

Reinforcement Learning-based Dynamic Weapon Assignment to Multi-Caliber Long-Range Artillery Attacks (다종 장사정포 공격에 대한 강화학습 기반의 동적 무기할당)

  • Hyeonho Kim;Jung Hun Kim;Joohoe Kong;Ji Hoon Kyung
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.45 no.4
    • /
    • pp.42-52
    • /
    • 2022
  • North Korea continues to upgrade and display its long-range rocket launchers to emphasize its military strength. Recently Republic of Korea kicked off the development of anti-artillery interception system similar to Israel's "Iron Dome", designed to protect against North Korea's arsenal of long-range rockets. The system may not work smoothly without the function assigning interceptors to incoming various-caliber artillery rockets. We view the assignment task as a dynamic weapon target assignment (DWTA) problem. DWTA is a multistage decision process in which decision in a stage affects decision processes and its results in the subsequent stages. We represent the DWTA problem as a Markov decision process (MDP). Distance from Seoul to North Korea's multiple rocket launchers positioned near the border, limits the processing time of the model solver within only a few second. It is impossible to compute the exact optimal solution within the allowed time interval due to the curse of dimensionality inherently in MDP model of practical DWTA problem. We apply two reinforcement-based algorithms to get the approximate solution of the MDP model within the time limit. To check the quality of the approximate solution, we adopt Shoot-Shoot-Look(SSL) policy as a baseline. Simulation results showed that both algorithms provide better solution than the solution from the baseline strategy.

Exact Algorithm for the Weapon Target Assignment and Fire Scheduling Problem (표적 할당 및 사격순서결정문제를 위한 최적해 알고리즘 연구)

  • Cha, Young-Ho;Jeong, BongJoo
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.42 no.1
    • /
    • pp.143-150
    • /
    • 2019
  • We focus on the weapon target assignment and fire scheduling problem (WTAFSP) with the objective of minimizing the makespan, i.e., the latest completion time of a given set of firing operations. In this study, we assume that there are m available weapons to fire at n targets (> m). The artillery attack operation consists of two steps of sequential procedure : assignment of weapons to the targets; and scheduling firing operations against the targets that are assigned to each weapon. This problem is a combination of weapon target assignment problem (WTAP) and fire scheduling problem (FSP). To solve this problem, we define the problem with a mixed integer programming model. Then, we develop exact algorithms based on a dynamic programming technique. Also, we suggest how to find lower bounds and upper bounds to a given problem. To evaluate the performance of developed exact algorithms, computational experiments are performed on randomly generated problems. From the results, we can see suggested exact algorithm solves problems of a medium size within a reasonable amount of computation time. Also, the results show that the computation time required for suggested exact algorithm can be seen to increase rapidly as the problem size grows. We report the result with analysis and give directions for future research for this study. This study is meaningful in that it suggests an exact algorithm for a more realistic problem than existing researches. Also, this study can provide a basis for developing algorithms that can solve larger size problems.

Approximate Dynamic Programming Based Interceptor Fire Control and Effectiveness Analysis for M-To-M Engagement (근사적 동적계획을 활용한 요격통제 및 동시교전 효과분석)

  • Lee, Changseok;Kim, Ju-Hyun;Choi, Bong Wan;Kim, Kyeongtaek
    • 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.

Random Forest Method and Simulation-based Effect Analysis for Real-time Target Re-designation in Missile Flight (유도탄의 실시간 표적 재지정을 위한 랜덤 포레스트 기법과 시뮬레이션 기반 효과 분석)

  • Lee, Han-Kang;Jang, Jae-Yeon;Ahn, Jae-Min;Kim, Chang-Ouk
    • 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.