A Genetic Algorithm for Uav Routing Integrated with a Parallel Swarm Simulation

The research focuses on optimizing the routing and simulation of UAV swarms, framing the problem within the NP-Complete Vehicle Routing Problem. By employing genetic algorithms, the study offers a fast and reliable solution for both static and dynamic routing scenarios. Utilizing Reynolds' swarm models and simulating on a Beowulf cluster with SPEEDES, the findings demonstrate that the genetic algorithms yield efficient results across various benchmarks. The analysis shows significant improvement in solution quality over time, making this approach suitable for UAV routing applications.