In　semiconductor　manufacturing　workshop，the　machine　states　are　often　inconsistent　when　the　products　re-enter　the　machine．　The　traditional　reentrant　scheduling　methods　are　unsuitable　for　semiconductor　workshop　scheduling　because　of　the　characteristic　of　inconsistent．According　to　the　characteristics　of　semiconductor　workshop，the　multi-objective　reentrant　hybrid　flow　shop　scheduling　problem　for　the　semiconductor　manufacturing　workshop　was　proposed．A　mathematical　model　of　this　problem　was　built　based　on　minimizing　the　maximum　completion　time，reducing　product　failure　rate　and　decreasing　machine　process　switching　times．An　optimal　foraging　algorithm　based　on　substantial　uncertainty　factor　(SUF_OFA)　was　proposed．In　proposed　algorithm，the　grey　correlation　analyzing　and　the　Pythagorean　fuzzy　set　of　MYCIN　uncertainty　factor　were　used　to　build　the　multi-objective　processing　strategy．The　substantial　uncertainty　factors　of　Pareto　solutions　were　adopted　as　the　fitness　value　of　the　optimal　foraging　algorithm．The　workpiece　number　was　used　as　the　coding　scheme，and　the　feasible　scheduling　solution　was　decoded　by　the　three-stage　decoding　method．Through　different　experiments　and　a　semiconductor　workshop　case，the　proposed　algorithm　was　compared　with　four　other　algorithms．The　proposed　model　was　verified　and　the　performance　of　the　proposed　algorithm　was　analyzed．The　results　show　that　SUF_OFA　has　significant　advantages　in　solving　the　multi-objective　reentrant　hybrid　flow　shop　scheduling　problem.　©　2023　Huazhong　University　of　Science　and　Technology.　All　rights　reserved.