Suitability of genetic based exploration in the creative design process

Abstract

Finding creative solutions to design problems depends heavily on a fruitful exploration in early phases. Many aspects of evolutionary computation (EC) and in particular genetic algorithms (GA) make them highly suited as computational tools for discovering good solutions. This paper discusses specific aspects of the GA method which parallel traditional design methodologies described by creativity researchers including Gordon, deBono, Parnes, and Osborn among others. Because EC methods work with populations of ‘fairly good’ solutions, there is less danger that creativity will be harmed by design fixation, on one ‘best’ solution. An example application is demonstrated using the design of a small truss bridge. The solutions offered by the application are varied enough to allow the designer a choice of forms. At the same time, all of the solutions offered are ‘fairly good’. This demonstrates the aspects of EC which make it well suited for creative exploration of problems.

Keywords:

• genetic algorithms
• evolutionary computation
• design exploration
• optimisation
• morphology