This book provides the current research on optimization methods for cooperative task allocation problems in drone fleets. Drone fleets, with their advantages of low cost, small size, and strong maneuverability, have been widely used in logistics, inspections, and other fields. However, it is a great challenge to cooperative task allocation when drone fleets are in large-scale tasks with task time constraints, temporal relationships, and performance requirements. To avoid the waste of resources and the conflicts of task, time, and space in drone fleets, it is important to ensure scientific and efficient task allocation in drone fleets. Various optimization problems in practical application scenarios are presented, including the heuristic method for task allocation in multirotor drones under wind influence, a multi-objective optimization method for task allocation in heterogeneous drones, a game-theoretic method for task allocation in the drone fleet, and a cooperative task allocation method for drone fleets with the assistance of a vehicle.

This book provides a pedagogical lesson for students, particularly Ph.D. students in operational research, but also acts as a research reference for senior researchers. Non-experts who are interested in the management of drone fleets can also gain interesting insights from this book.

Autorentext

He Luo

Professor and Ph.D. advisor at Hefei University of Technology, focusing on research in key technologies for drone fleet cooperative optimization and intelligent decision-making. He has published over 70 academic papers, received 3 U.S. patents, more than 50 Chinese national invention patents, and holds over 10 software copyrights.

Xiaoxuan Hu

Professor and Ph.D. advisor at Hefei University of Technology, primarily engaged in research on system modeling and optimization, as well as aerospace system management. He has published over 70 academic papers in domestic and international journals and holds more than 100 authorized invention patents.

Guoqiang Wang

Associate Professor and Ph.D. supervisor at Hefei University of Technology. His research areas include the generation of communication topology and dynamic optimization for drone fleets, as well as cooperative path planning for vehicles and UAVs. He has published over 20 academic papers, received 2 U.S. patents and 27 Chinese national invention patents as the first inventor, and holds 3 software copyrights.

Yingying Ma

Postdoctoral researcher at Hefei University of Technology, specializing in research on drone fleet task allocation and target assignment methods, focusing on the design of heuristic and metaheuristic algorithms to effectively optimize task efficiency and coordination in complex systems.