| Article ID: | iaor20133781 |
| Volume: | 48 |
| Issue: | 1 |
| Start Page Number: | 187 |
| End Page Number: | 199 |
| Publication Date: | Jul 2013 |
| Journal: | Structural and Multidisciplinary Optimization |
| Authors: | Keane Andy, Nasuf Alkin, Bhaskar Atul |
| Keywords: | heuristics: genetic algorithms |
We propose an automated shape generative framework, which provides an alternative way of exploring the design space in a structural mechanics context. The framework presented uses ‘blind’ evolutionary intelligence to synthesise shape grammar sentences i.e. Grammatical Evolution (GE), where rules are selected by a Genetic Algorithm (GA). This is a novel approach to automate the Shape Grammar (SG) formalism. We then present an application of a grammar based shape generative framework to solve a 2D design optimisation problem. This involves synthesis of parametric 2D curves where the shape grammar primitives are introduced as arcs represented by rotation and a radius. The efficacy of the proposed shape generative framework is then compared with that of Non‐Uniform Rational B‐Splines (NURBS) parametrisation for structural optimisation.