In　this　paper,　we　propose　a　collaborative　differential　evolution　algorithm　(CODE)　to　solve　the　problem　of　the　multiple　unmanned　aerial　vehicles　(multi-UAVs)　path　planning　in　the　three-dimensional　(3D)　environment.　Because　the　centralized　differential　evolution　algorithm　(DE)　solves　the　multi-UAVs　path　planning　problem,　the　dimension　is　too　high　and　the　amount　of　computation　is　too　large,　CODE　divides　the　entire　population　of　DE　into　several　groups　equally,　and　each　group　searches　in　parallel,　calculates　the　individual　cost　of　each　UAVs　and　establishes　an　information　exchange　mechanism　to　calculate　the　cooperation　cost　between　UAVs,　and　outputs　the　path　corresponding　to　a　UAV.　Experimental　results　show　that　the　proposed　algorithm　is　significantly　better　than　other　comparative　algorithms.　©　2023,　The　Author(s),　under　exclusive　license　to　Springer　Nature　Switzerland　AG.