Intelligent Optimization Methods for Unmanned Cluster Delivery Support Task Allocation

To enhance the efficiency of material distribution for battlefield unmanned platform delivery support tasks, research was conducted on the task allocation issues of unmanned platforms, aiming to improve the military’s material support capability during wartime. Firstly, a VRPTW model based on unmanned platform delivery was constructed, considering the limitations of the unmanned platform’s endurance mileage, rated load capacity, and intermediate charging. Subsequently, an improved genetic algorithm was employed to optimize the flight paths to minimize the total flight cost. Through simulation and validation of a specific battlefield material delivery support task, effective flight path planning solutions were obtained. The research findings demonstrate that this method is both efficient and feasible, providing some guidance and support for enhancing the military’s material support capability and strengthening operational effectiveness.