This　paper　considers　the　unmanned　aerial　vehicle　(UAV)　global　path　planning　as　an　optimization　problem　with　multiple　constraints　and　proposes　an　improved　fireworks　algorithm　(FWA)　and　particle　swarm　optimization　(PSO)　cooperation　algorithm　to　generate　an　optimal　path.　The　objective　function　of　the　UAV　flight　path　is　modeled　to　have　the　shortest　length　satisfying　strict　multiple　threat　area　constraints.　The　aconstrained　method　using　the　level　comparison　strategy　is　integrated　into　both　FWA　and　PSO　to　enhance　their　superior　constraint-handling　ability.　To　increase　the　population　diversity,　the　whole　population　is　divided　to　fireworks　and　particles,　which　perform　search　operation　in　parallel.　A　new　mutation　strategy　in　the　fireworks　is　adopted　to　avoid　falling　into　the　local　optimum.　Information　sharing　mechanism　between　fireworks　and　particles　isestablished　to　make　the　population　achieve　the　excellent　global　optimization　performance.　Several　numerical　simulations　are　carried　out　and　the　results　show　that　our　proposed　algorithm　performs　well　in　obtaining　high　quality　solutions　and　handling　constraints.　(C)　2021　Elsevier　Masson　SAS.　All　rights　reserved.