The　lines　optimisation　of　an　underwater　vehicle　based　on　a　dynamic　surrogate　model　is　studied.　Four　performances　including　rapidity,　manoeuverability,　energy　consumption　and　structure　of　the　underwater　vehicle　are　considered　in　the　optimisation　framework　constructed　by　a　generalised　collaborative　optimisation　method.　Expert　knowledge　based　analytic　hierarchy　process　is　conducted　to　obtain　the　optimisation　object　that　involves　the　four　performances.　Numerical　simulation　is　performed　to　accurately　analyze　the　rapidity,　manoeuverability　and　structure　performances　of　the　underwater　vehicle.　To　reduce　the　calculation　burden,　dynamic　surrogate　models　are　proposed　to　replace　numerical　simulation　in　the　optimisation　framework.　To　guarantee　the　optimisation　efficiency　and　accuracy,　a　synthetic　minority　oversampling　technique　(SMOTE)　and　adaptive　minimise　lower　confidence　bound　(LCB)　are　combined　in　constructing　the　dynamic　surrogate　models.　The　proposed　optimisation　strategy　is　applied　to　the　SUBOFF　model　and　compared　with　other　dynamic　surrogate　models.　Comparison　results　prove　the　advantages　of　the　proposed　dynamic　surrogate　model.　©　2022　Informa　UK　Limited,　trading　as　Taylor　&　Francis　Group.