Red-billed blue magpie optimizer: a novel metaheuristic algorithm for 2D/3D UAV path planning and engineering design problems

Abstract Numerical optimization, Unmanned Aerial Vehicle (UAV) path planning, and engineering design problems are fundamental to the development of artificial intelligence. Traditional methods show limitations in dealing with these complex nonlinear models. To address these challenges, the swarm intelligence algorithm is introduced as a metaheuristic method and effectively implemented. However, existing technology exhibits drawbacks such as slow convergence speed, low precision, and poor robustness. In this paper, we propose a novel metaheuristic approach called the Red-billed Blue Magpie Optimizer (RBMO), inspired by the cooperative and efficient predation behaviors of red-billed blue magpies. The…

• NN
  National Natural Science Foundation of China

  Award: 52165063
• GS
  Guizhou Science and Technology Department

  Award: Qiankehe pingtai rencai-GCC [2022] No.006-1, Qiankehe support normal [2023] No.348 and No.309, Qiankehe support normal [2022] No.165 and No.008
• NS
  Natural Science Foundation of Chongqing

  Award: CSTB2022NSCQ-MSX1600