Research on optimization method of combat effectiveness based on AHP-DQN

Abstract

In view of the case that the fleet of ships threatens the safety of the sea area, the scenarios of red side penetration attack, blue side air defense and antimissile, as well as three kinds of anti aircraft carrier combat strategies of land, sea and air are designed. Based on the Mozi system, the multi scheme combat simulation is carried out, and the battle damage data of both sides are obtained. On this basis, an index system based on the performance parameters of decoy and attack is established, and the operational effectiveness of the three strategies is analyzed with the analytic hierarchy process (AHP). Furthermore, a Deep Reinforcement Learning (DRL) algorithm based on AHP weight is proposed, which optimizes the sea based strategy and improves the combat effectiveness by 5.36%. The research results show that the method of scenario design, combat strategy simulation, and AHP-DQN for operational efficiency optimization based on such combat simulation software as Mozi system can provide reference for anti-ship warfare.

Keywords

• operational rehearsal|strike strategy|analytic hierarchy process|deep reinforcement learning|efficiency optimization