Joint Fire Attack Mission Planning Method Based on Intelligent Confrontation Evolution

doi:10.3969/j.issn.1000-1093.2019.06.020

Abstract

Abstract: In view of the fact that the conventional joint fire attack mission planning method rarely involves an issue of friend-foe confrontation leading to the change in evaluation environment, a smart confrontation evolution algorithm based on the evolution of friend-foe confrontation is proposed. The proposed algorithm is based on genetic algorithm, in which the simulation of biological competition mechanism is introduced into the two populations of friend and foe for implementing the confrontational evolution. An observe-orient-decide-act (OODA) super-network is constructed based on the battlefield situation map, and then the OODA cycle efficiency is calculated to determine the order of friend and foe attacks. The task-planning optimal individuals can adapt to the dynamic changes of the battlefield through the confrontation evolution of multiple generations. The simulated results show that the multi-generation evolutionary optimal individual has stronger dynamic adaptability, and the joint firepower strike rate is higher. The response mechanism to respond to the emergencies is more perfect, which can effectively solve the evaluation optimization issues of joint firepower mission planning. Key

Key words: jointfireattack, missionplanning, intelligentconfrontationevolution, geneticalgorithm, super-network, observe-orient-decide-actcycle, artificialintelligence

CLC Number:

E837

LIU Hao，ZHANG Ce，DING Wentao. Joint Fire Attack Mission Planning Method Based on Intelligent Confrontation Evolution[J]. Acta Armamentarii, 2019, 40(6): 1287-1296.

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第40卷第6期
2019 年6月兵工学报ACTA
ARMAMENTARIIVol.40No.6Jun.2019

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