In practical system identification, process optimization and controller design, it is often desirable to simultaneously handle several objectives and constraints. In some cases, these objectives and constraints are non-commensurable and they are not explicitly/mathematically available. This paper proposes a new subjective optimization method based on Interactive Evolutionary Computation (IEC) to handle these problems. IEC is an evolutionary algorithm whose fitness function is provided by human users. The whole approach has been implemented in MATLAB (EAsy-IEC Toolbox) and applied to two case-studies: tuning a Model Predictive Controller and temperature profile design of a batch beer fermenter. The results show that IEC is an efficient and comfortable method to incorporate the prior knowledge of the user into optimization problems. The developed EASyIEC Toolbox (for Matlab) can be downloaded from the website of the authors: http://www.fmt.vein.hu/softcomp/EAsy. Key words: Interactive E...