Method for scheduling UAVs based on chaotic adaptive firefly algorithm

摘要

#$%^&*AU2020101065A420200723.pdf#####ABSTRACT The present invention belongs to the technical field of scheduling policies for unmanned aerial vehicles (UAVs), and in particular, to a method for scheduling UAVs based on a chaotic adaptive firefly algorithm (CAFA). In order to appropriately assign missions to get the most benefit when there are a relatively large number of missions and UAVs, the following solution is proposed, including the following steps: establishing a model, where mission assignment and scheduling of UAVs can be defined as an optimization model: a group of UAVs { = ,2, , Vm and a group of to-be-completed missions is m 2s ' ", a mission risk index and a flight cost index indicate system costs, a mission completion potential index and a mission execution value index indicate system benefits, and a model evaluation index is used to evaluate a current assignment scheme; and optimizing a step factor, and using an adaptive stepsize to accelerate convergence and improve the accuracy. In the present invention, experimental results show that the algorithm can improve a response speed and the efficiency of a multi-UAV system. Compared with a particle swarm algorithm and a classical firefly algorithm, the accuracy of the algorithm is improved by 12.4% and 12.05%, respectively; and a rate of convergence of the algorithm is increased by 22.8% and 7.53%, respectively.1/3 Start Generate an initial population according to an initial solution Initialize various parameters Generate individual fitness of fireflies (light intensity of the fireflies) by using a chaos method Calculate positions of the fireflies according to formulas of an adaptive stepsize and an inertia coefficient The fireflies move according to relative brightness and the positions No 'enerate relative brightness of the fireflies according to updated positions of the fireflies by using a mutative-scale chaos method ether the maximum number fiterations or convergence is reached? Yes Output an optimal solution End FIG. 1