In　this　study,　an　optimization　design　of　crankshaft　bearing　of　rotate　vector　(RV)　reducer　was　proposed　based　on　genetic　algorithm.　First,　based　on　fatigue　life　theory,　the　service　life　of　crankshaft　bearing　of　reducer　was　modeled.　Considering　the　bearing　structural　parameters　as　design　variables,　optimizated　design　was　established　with　the　objective　of　attaining　improved　fatigue　life,　torsional　stiffness,　and　bearing　gap　volume.　Then,　the　effects　of　structural　parameters　on　reducer　performance　were　systematically　analyzed.　Next,　based　on　genetic　algorithm,　the　optimizations　for　single-,　double-,　three-objective　models　were　performed　with　the　corresponding　constraints.　Finally,　the　representative　result　was　selected　from　Pareto　optimal　solutions　of　three-objective　optimization,　the　parameters　of　bearing　structure　and　performance　before　and　after　optinization　were　compared　and　analyzed.　The　results　show　that　the　effective　improvement　in　bearing　performance　through　the　proposed　optimization　method,　which　presents　the　academic　significance　for　improving　the　comprehensive　performance　of　RV　reducer.