UAV Path Planning Based on Hybrid Differential Evolution with Fireworks Algorithm

This paper considers the unmanned aerial vehicle (UAV) global path planning as an optimization problem with constraints and proposes a hybrid differential evolution with firework algorithm (HDEFWA) to generate the optimal feasible path. The multiple constraints based on the realistic scenarios are taken into account, including terrain and threat area constraints. The hybrid algorithm integrates the differential evolution operator into the mechanism of optimizing the fireworks algorithm (FWA) and uses the ideas of mutation, crossover, and selection to transform the spark particles generated by the explosion. The source of the differential mutation operator is the excellent particles in the iterative population. This mechanism makes up for the basic firework algorithm's neglect of the excellent solution resources in the population, which greatly improves the information sharing among the solutions. Experiments show that the proposed hybrid algorithm is superior to other intelligent algorithms in UAV path planning.