Research on vehicle assignment model for constraints handling based on computational intelligence algorithms

The task allocation of unmanned aerial vehicle (UAV) is a complex assignment problem with various constraints. With the increase of the size of scenarios and the number of constraints, UAV assignment problems become more complicated. Especially, the potential dimensional explosion and optimization difficulty are unavoidable to those algorithms based on linear programming. A new UAV assignment model was proposed, which transforms the UAV assignment problem into a multi-constraint optimization problem. The proposed model reduces the dimension of solution space effectively, improves the optimization efficiency, and is adapted to the other computational intelligence algorithms. Several computational intelligence algorithms, such as particle swarm optimization, genetic algorithm, differential evolution algorithm, clonal selection algorithm, were applied to accomplish the optimization work. Numerical experimented results illustrate that the model has better adaptability and extensibility, can solve complex UAV assignment problems combined with the computational intelligence algorithms.