A Path-Planning Method Recommended for Multi-UAV Police Patrols Based on the Wolf Pack Optimization Algorithm Using CDRS and DRSS

Multi-UAV path planning for police patrols plays an important role in public security work, and while many path-planning algorithms have been applied in this area, all of them possess various degrees of shortcomings. To further improve the accuracy and efficiency of multi-UAV path planning for police patrols, this paper proposes a multi-UAV police patrol path-planning method based on an improved wolf pack optimization algorithm using the strategies of Composite Directional Raid and Dynamic Random Search (PMU-3PM-IWPA). Firstly, a multi-UAV police patrol path-planning model was constructed to reflect the planning problem for multi-UAV police patrol paths (PMU-3PM). Moreover, to enhance the performance of the existing wolf pack optimization algorithm, this paper proposes an improved wolf pack optimization algorithm (for short CDR-DRS-WPOA), including the Composite-Directional Raid Strategy (CDRS), aimed at enhancing global exploration capability, as well as the Dynamic Random Search Strategy (DRSS), with a view to speeding up the convergence for simple problems and heightening the optimization accuracy for difficult problems. Finally, the improved wolf pack optimization algorithm was adopted to solve the issue of multi-UAV path planning for police patrols, and numerical experiments were carried out on 20 public classical datasets as well as PMU-3PM compared with GA, PSO, WDX-WPOA, and DAF-BRS-CWOA. The results indicate that CDR-DRS-WPOA took 20~80% less time and possessed more optimization accuracy, and that PMU-3PM-IWPA based on CDR-DRS-WPOA offers excellent performance.