A　parallel　multidisciplinary　optimization　design　is　proposed　for　the　lines　design　of　an　underwater　vehicle.　Resistance　and　energy　consumption　are　concerned　about　in　obtaining　the　optimized　lines.　Collaborative　optimization　strategy　is　adopted　to　construct　the　optimization　framework.　The　simulated　annealing　algorithm　in　combination　of　the　modified　method　of　feasible　directions　are　taken　as　the　optimization　algorithms.　CFD　based　simulation　is　conducted　to　analyze　the　resistance　of　the　underwater　vehicle.　To　improve　the　optimization　efficiency,　a　surrogate　model　is　incorporated　into　the　optimization　framework　to　approximate　the　CFD　calculation.　Unlike　the　conventional　static　surrogate　models　used　in　the　design　of　underwater　vehicles,　a　dynamic　surrogate　based　on　trust　region　and　lower　confidence　bound　is　proposed.　An　adaptive　balance　parameter　is　taken　in　the　lower　confidence　bound　approach　to　guarantee　the　tradeoff　between　the　exploitation　and　exploration　ability　of　the　dynamic　surrogate　model.　Optimal　Latin　hypercube　algorithm　is　employed　as　the　method　of　design　of　experiments.　Radial　basis　function　is　employed　to　construct　the　surrogate　model.　SUBOFF　model　is　used　to　demonstrate　the　proposed　optimization　scheme.　Lines　of　the　underwater　vehicle　are　determined　and　optimization　results　of　the　resistance　and　energy　consumption　show　the　effectiveness　of　optimization　scheme.