  The use of evolutionary methods in design and art is increasing in diversity
and popularity. Approaches to using these methods for creative production
typically focus either on optimisation or exploration. In this paper we
introduce an evolutionary system for design that combines these two approaches,
enabling users to explore landscapes of design alternatives using
design-oriented measures of fitness, along with their own aesthetic
preferences. We test our methods using a biologically-inspired generative
system capable of producing 3D objects that can be exported directly as 3D
printing toolpath instructions. For the search stage of our system we combine
the use of the CMA-ES algorithm for optimisation and linear interpolation
between generated objects for feature exploration. We investigate the system`s
capabilities by evolving highly fit artefacts and then combining them with
aesthetically interesting ones.
