Modeling the series of military actions to plan an attack mission of a swarm drones

The use of unmanned aerial vehicles (UAVs) has become an innovative technological tool in modern hybrid warfare. The effectiveness of UAVs has increased dramatically when combat drones are deployed in swarms to attack enemy targets. The creation of an active shield in the air to help the military on the ground allows for the integration of air and ground combat operations, which gives a new synergistic effect to the use of attack drones. Therefore, it is relevant to conduct a study on the planning of attack missions using attack UAVs. The subjects of this research are models used to plan attacking military operations using attack drones. The purpose of this study is to create a set of models that enable planning massive attacks by attack drones. Tasks to be solved: to form a sequence of military actions for an attack mission; to justify the choice of local military zones for an attack; to form the combat potential of a swarm of drones; to justify the use of simulator drones to deplete enemy resources; to form waves of a swarm of attack drones; to model the movement of the swarm to the targets. The mathematical methods and models used are: system analysis to form an attack mission of attack drones; method of virtual experiment to select important indicators of enemy activity; method of qualitative assessment of enemy actions; method of lexicographic ordering of options to select relevant military local zones for attack; integer (Boolean) optimization to create the necessary combat potential to defeat enemy targets; simulation multi-agent modeling of the flight of a swarm of attack drones. The following results were obtained: a systematic representation of the sequence of military actions for conducting an attack by attack drones was obtained; indicators of enemy activity were substantiated; a set of actual military local zones with enemy targets was formed; a swarm of simulator drones was created to distract the enemy; the necessary combat potential of the attack drone swarm was formed; waves of attack drones were substantiated to defeat enemy targets; and a simulation, multi-agent model of swarm movement was created. Conclusions. The results of the study make it possible to substantiate a plan of combat operations using a swarm of attack drones, which contributes to the effectiveness of operational and tactical actions on battlefields. The novelty of the proposed approach lies in the scientific substantiation of the sequence of military actions for planning the attack mission of attack drones, using the developed set of original and new mathematical and simulation models.