关键词: 关键词:野狗优化算法, 分段线性混沌映射, 秃鹰俯冲机制, 螺旋搜索因子

Abstract: Abstract: Aiming at the problems of slow convergence speed and low optimization accuracy of dingo optimization algorithm （DOA）， an improved dingo optimization algorithm （IDOA） based on PWLCM and the bald eagle’s swooping mechanism is proposed. Firstly， a piecewise linear chaotic map with eriodicity is used to initialize the dingo population， effectively increasing the diversity of the dingo population. Secondly， the bald eagle’s swooping mechanism is introduced into the persecution strategy to  accelerate the speed of prey capture and strengthen the ability of the algorithm to explore local areas. Finally， the spiral search factor is introduced into the scavenger strategy to enhance the local development and exploration ability of the algorithm， so as to further improve the optimization speed and accuracy of the algorithm. Simulation experiment data， ablation experiment and Wilcoxon rank sum test all show that the proposed IDOA has better optimization speed and optimization accuracy than other comparison algorithms； Compared to other improved dingo optimization algorithms， the proposed IDOA shows better overall performance.

Key words: Key words: dingo optimization algorithm, piecewise linear chaotic map, bald eagle’s swooping mechanism, spiral search factor