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UAV Cooperative Multiple Task Assignment Based on Discrete Particle Swarm Optimization

The combinatorial optimization problem of assigning cooperating unmanned aerial vehicles to multiple tasks is posed by a shared model. A discrete particle swarm optimization algorithm for solving such a problem is proposed. A matrix representation of the algorithm's position vector spaces is employed. A new update strategy for the position and speed of particle is applied in this algorithm. The performance of the algorithm is compared to that of particle swarm optimization algorithm and genetic algorithm for two different cost functions. Simulation results demonstrated the effectiveness and feasibility of the proposed approach.