A Benchmark for Multi-UAV Task Assignment of an Extended Team Orienteering Problem
This provides a benchmark for researchers and practitioners working on multi-UAV task assignment, but it is incremental as it applies existing methods to a new problem formulation.
The authors tackled the problem of multi-UAV task assignment by modeling an extended Team Orienteering Problem and evaluating three intelligent algorithms (Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization) through experiments with different settings, resulting in a benchmark for assessing algorithms in this domain.
A benchmark for multi-UAV task assignment is presented in order to evaluate different algorithms. An extended Team Orienteering Problem is modeled for a kind of multi-UAV task assignment problem. Three intelligent algorithms, i.e., Genetic Algorithm, Ant Colony Optimization and Particle Swarm Optimization are implemented to solve the problem. A series of experiments with different settings are conducted to evaluate three algorithms. The modeled problem and the evaluation results constitute a benchmark, which can be used to evaluate other algorithms used for multi-UAV task assignment problems.