Abstract: To improve the ability of scientifically assessing the sector control complexity, a clustering algorithm of sector con鄄
trol complexity based on the coyote optimization algorithm (COA) is proposed in this paper. Firstly, a per-dimen鄄
sion mutation improvement strategy is introduced to propose the improved coyote optimization clustering algorithm
(ICOCA), which can solve the problem of being easily trapped in local optimal solutions. Secondly, taking the re鄄
gional control sectors in the Northwest China as the research object, the ICOCA is applied to conduct cluster analy鄄
sis for the index of sector control complexity. Finally, the results of sector clustering are simulated and verified,
which can prove the effectiveness and reliability of the proposed algorithm in the classification of sector control
complexity, thus it can provide effective data decisions for subsequent airspace management.

Key words: air traffic management, control complexity, cluster analysis, improved coyote optimization clustering algo－
rithm (ICOCA)