To　obtain　high-quality　solutions　and　good　performance　solution　sets　during　the　optimization　of　many-objective　Permutation　Flow-shop　Scheduling　Problems(PFSP),　a　positive　projection　grey　target　model　with　comprehensive　objective　weight　was　proposed　based　on　grey　target　theory,　which　could　overcome　the　shortcoming　of　obtaining　information　in　the　optimization　process.　A　PFSP　mathematical　model　with　four-objective　and　a　grey　target　model　in　the　field　of　multi-objective　optimization　were　defined,　then　target　distance　was　calculated　to　judge　the　pros　and　cons　of　Pareto　front　and　to　extract　the　uncertainty　information　among　the　objective　function　values.　To　solve　the　different　target　distances　of　Pareto　front　in　same　section　plane　and　to　get　more　information　in　the　solution　space,　a　Positive　Projection　Grey　Target(PPGT)model　was　proposed.　Further,　to　acquire　the　information　of　the　volatility　and　the　correlation　among　the　objective　function　values,　a　novel　comprehensive　objective　weight　method　based　on　CRITIC　method　and　entropy　weight　method　was　introduced　into　PPGT　model.　The　modified　PPGT　model　was　integrated　into　the　genetic　algorithm　to　solve　the　multi-objective　PFSP.　The　effectiveness　of　the　proposed　method　was　verified　by　three　sets　of　experiments　and　four　comparison　algorithms.　©　2022,　Editorial　Department　of　CIMS.　All　right　reserved.