This paper presents a 3-D optimization of a moderately loaded transonic compressor rotor by means of a multi-objective optimization system. The latter makes use of a Differential Evolutionary Algorithm in combination with an Artificial Neural Network and a 3D Navier-Stokes solver. Operating it on a cluster of 30 processors enabled the optimization of a large design space composed of the tip camber line and spanwise distribution of sweep and chord length. Objectives were an increase of efficiency at unchanged stall margin by controlling the shock waves and off-design performance curve. First, tests on a single blade row allowed a better understanding of the impact of the different design parameters. Forward sweep with unchanged camber improved the peak efficiency by only 0.3% with a small increase of the stall margin. Backward sweep with an optimized S shaped camber line improved the efficiency by 0.6% with unchanged stall margin. It is explained how the camber line control could introduce the forward sweep effect and compensate the negative effects of the backward sweep. The best results (0.7% increase in efficiency and unchanged stall margin) have been obtained by a stage optimization that also considered the spanwise redistribution of the rotor flow and loading to reduce the Mach number at the stator hub.
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