The　manufacturing　industry　in　China　is　undergoing　a　digital　and　green　low-carbon　transformation.　To　achieve　energy　saving　and　emission　reduction　and　improve　the　equipment　utilization　rate,　a　mathematical　model　of　the　hybrid　flow-shop　scheduling　problem　considering　the　joint　of　machine　and　automated　guided　vehicle　(AGV)　with　renewable　energy　(HFSP-MA-RE)　was　established.To　resolve　this　model,　a　joint　scheduling　strategy　and　an　energy　distribution　strategy　of　machines　and　AGVs　based　on　advance　scheduling　were　proposed.　In　the　case　of　AGV　path　optimization　and　charging　constraints,　four　objectives　of　the　maximum　completion　time,　carbon　emissions,　total　energy　consumption,　and　AGV　utilization　rate　were　optimized.The　multi-objective　optimal　foraging　algorithm　based　on　a　positive　projection　gray　target　(PPGT_OFA)　was　constructed　to　resolve　this　problem.　Through　twenty-four　test　cases　and　one　engineering　application,　the　proposed　algorithm　and　five　multi-objective　optimization　algorithms　were　tested　to　verify　the　effectiveness　of　the　HFSP-MA-RE　model　and　PPGT_OFA　in　solving　this　multi-objective　optimization　problem.　©　2025　Beijing　University　of　Aeronautics　and　Astronautics　(BUAA).　All　rights　reserved.