In this paper we examine how multi-objective evolutionary algorithms can assist in design space exploration. In this approach an engineer specifies certain hard and soft performance requirements for a multi-processor system, and allows it to be generated automatically by competitive evolution/optimisation, thus obviating the need for detailed design. To make the proposal concrete, we use the Intel IXP1200 network processor as a baseline complex system design and show how various improvements can be make to this architecture by evolutionary/competitive design. Various approaches to multi-objective optimisation (Darwin, Lamarck Baldwin, etc.) are compared and contrasted in their ability to generate architectures meeting various constraints. Our paper highlights the flexibility that this approach bestows on the designer, along with the potential to achieve cost savings and performance improvement.