This paper shows that it is possible to (1) discover novel implementations of median circuits using evolutionary techniques and (2) find out suitable median circuits in case that only limited resources are available for their implementation. These problems are approached using Cartesian genetic programming and an ordinary compare–swap encoding. Combining the proposed approaches a method is demonstrated for effective exploration of the design space of median circuits under various constraints.