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This paper describes a generative evolutionary design system that aims to fulfil two key requirements: customisability and scalability. Customisability is required in order to allow the design team to incorporate personalised and idiosyncratic rules and representations. Scalability is required in order to allow large complex designs to be generated and evolved without performance being adversely affected. In order to fulfil these requirements, a computational architecture has been developed that differs significantly from existing evolutionary systems. In order to verify the feasibility of the this architecture, the generative process capable of creating three-dimensional building models has been implemented and demonstrated.
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... The generative evolutionary design system is currently under development. For a detailed description of this system, see (Janssen 2004;Janssen et al. 2005). This system would be used during the design development phase, in order to evolve alternative designs. ...
This paper describes a generative evolutionary design method, called the ‘schema method’, which requires the design team to participate in the programming of generative and evolutionary rules and representations. The method consists of two phases: in the first phase, the design team develops and encodes the essential and identifiable character of the designs to be generated and evolved; in the second phase, the design team uses an evolutionary system to generate and evolve designs that incorporate this character. This method is based on a previous generative evolutionary design method, developed by John Frazer from the late 1960s onwards, called the ‘concept seeding method’.
The preconceptions that designers bring to the table when they are considering a particular design task are an unavoidable and necessary part of the design process. This paper first reviews the literature relating to the role of preconceptions in design, and then goes on to discuss computational tools that support the development and expression of such design preconceptions. As an example of such a tool, an outline is given of a generative evolutionary design system that allows designers to evolve families of designs that embody preconceived values and ideas.
The preconceptions that designers bring to the table when they are considering a particular design task are an unavoidable
and necessary part of the design process. This paper first reviews the literature relating to the role of preconceptions in
design, and then goes on to discuss computational tools that support the development and expression of such design preconceptions.
As an example of such a tool, an outline is given of a generative evolutionary design system that allows designers to evolve
families of designs that embody preconceived values and ideas.
We investigate the effect of global parallelism using a master
slave approach, on the behavior of a steady state genetic algorithm for
design optimization. Empirical results in several engineering design
domains demonstrate that this simple form of parallelism which has the
potential for almost linear speedup, does not significantly disturb the
convergence pattern of the GA, even when the number of processors is
comparable to the size of the population
Since the end of the last century it has commonly been seen as decadent to simply apply aesthetics to the structure of a building to make it beautiful (with the exception of the deliberately ironic, although irony itself would have been thought decadent by the stern moralists of the modern movement ). Architects such as Louis Sullivan, Mies Van der Rohe, Le Corbusier and so on used the example of engineering to help to explain the relationship between form and function. Based on the simplistic assumption that engineers do not design form, but that it emerges from the correct solution to mechanical realities (cf. the Eiffel tower, Brunel's bridges and the "dom-ino" concrete frame) the modern movement declared such objects as pure and right . The functionalist tradition has suffered many blows in the last 50 years, partly because it was always an oversimplification, and partly because technology has now reached a point where the constraints of structure have almost vanished, with form becoming the precursor of function rather than it's determinant, ie. anything is possible (cf. Utzon's Sydney Opera House, The new Bilbao gallery etc.) The study of evolutionary algorithms allows us to get back to a more rigorous analysis of the basic determinants of form, where the global form of an object not only should not but actually cannot be predetermined on an aesthetic whim. Thus with genetic algorithms we have an opportunity to experiment with the true determinants of form in a way that the pioneers of the modern movement would have relished - an aesthetic of pure function whose outcome is totally embedded in the problem to be solved. Published (author's copy) Peer Reviewed