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Adaptive PSO using random inertia weight and its application in UAV path planning

A novel particle swarm optimization algorithm, called APSO_RW is presented. Random inertia weight improves its global optimization performance and an adaptive reinitialize mechanism is used when the global best particle is detected to be trapped. The new algorithm is tested on a set of benchmark functions and experimental results show its efficiency. APSO_RW is later applied in UAV (Unmanned Aerial Vehicle) path planning.