This　paper　considers　the　unmanned　aerial　vehicle　(UAV)　global　path　planning　as　an　optimization　problem　with　constraints　and　proposes　a　hybrid　differential　evolution　with　firework　algorithm　(HDEFWA)　to　generate　the　optimal　feasible　path.　The　multiple　constraints　based　on　the　realistic　scenarios　are　taken　into　account,　including　terrain　and　threat　area　constraints.　The　hybrid　algorithm　integrates　the　differential　evolution　operator　into　the　mechanism　of　optimizing　the　fireworks　algorithm　(FWA)　and　uses　the　ideas　of　mutation,　crossover,　and　selection　to　transform　the　spark　particles　generated　by　the　explosion.　The　source　of　the　differential　mutation　operator　is　the　excellent　particles　in　the　iterative　population.　This　mechanism　makes　up　for　the　basic　firework　algorithm＇s　neglect　of　the　excellent　solution　resources　in　the　population,　which　greatly　improves　the　information　sharing　among　the　solutions.　Experiments　show　that　the　proposed　hybrid　algorithm　is　superior　to　other　intelligent　algorithms　in　UAV　path　planning.　©　2022,　Springer　Nature　Switzerland　AG.