The axial compressor is one of the most challenging components for aero engine design. The highly complex and multi-disciplinary design process is built up from several separate design phases differing with respect to the number of details. Typically, meanline prediction is the first step of the aerodynamic design process where the goal is to provide a first guess and proper choice of basic design parameters. As a preliminary design procedure it is one of the most important parts of the compressor design process since a poor design decision on these parameters cannot be corrected by subsequent development efforts. The design of a compressor is always a compromise between contradicting requirements like high efficiency, low number of stages and high surge margin. This is typical for multi-criterion optimization problems requiring a high number of design analyses and a well-designed procedure for finding trade-off solutions. The paper will show how to automate a given Rolls-Royce preliminary design process in order to find Pareto-optimal trade-off solutions for design conditions. The aspect of process acceleration is also an important goal to release the design engineer from time-consuming parameter studies. Essential elements for speeding up the design process are the use of modern process integration tools, multi-criterion decision concepts, and nonlinear programming algorithms. Results will be shown based on a given Rolls-Royce compressor design for multi-objective optimization with respect to maximum efficiency, maximum surge margin, and maximum overall pressure ratio, where different deterministic and stochastic algorithms are used.