RESEARCH OF ANT COLONY OPTIMIZATION ALGORITHMS AS A WAY TO EFFICIENTLY PLAN ROUTES FOR UNMANNED AERIAL VEHICLES

The article investigates the use of ant algorithms to solve the problem of routing unmanned aerial vehicles (UAV). The use of these algorithms to solve the task allows us to optimise computing costs and increase the eff iciency of fi nding optimal routes. The ant algorithms, based on the principles of self-organisation and stigmergy, demonstrate the ability to adapt to changing conditions and eff ectively solve complex optimisation problems with many variables. This approach paves the way for automated route planning for unmanned aerial vehicles, which helps to reduce the risks and costs of their operation.