Cooperative Task Assignment for Aerial-Ground Detection Systems via a Novel Hybrid Genetic Method

This study focuses on cooperative task assignment for aerial-ground detection systems utilizing a hybrid genetic algorithm (HGA) with dual-layer chromosomes. It addresses nonroad network constraints, task unreachability, and practical factors such as power, capacity, and waiting time. A mixed integer linear programming model is established for aerial-ground cooperative task assignment. A HGA with dual-layer chromosome encoding is designed to solve the aerial-ground cooperative task assignment problem quickly. In addition, the proposed method demonstrates shorter task durations and higher efficiency than the state-of-the-art algorithms. Finally, synthetic and real-world examples are provided to illustrate the effectiveness and advantages of the method gathered in the article.