@inproceedings {pub3097,
	title = {State-based Representation for Structural Topology Optimization and Application to Crashworthiness},
	author = {Nikola Aulig AND Markus Olhofer},
	year = {2016},
	month = {July},
	abstract = {Structural topology optimization is a valuable tool for designers and engineers to obtain concepts of mechanical structures early in a design process. When applying evolutionary algorithms to topology optimization, due to the high-dimensionality of a typical topology optimization problem the representation of the structure is especially important. In this work we propose a novel adaptive state-based representation, taking the phenotypic, physical state of the structure into account. Elements of the discretised design space are grouped based on local state features such as elemental energies or displacements. Each group is represented by a prototype element for which an covariance matrix adaptation evolution strategy optimizes an update signal, which determines the amount of material to be removed
or added. The new method is validated on the compliance minimization by reproducing a reference structure and subsequently applied to the industrial problem of crashworthiness topology optimization, for which can results in comparable or better structures compared to a industrial tool.},
	publisher = {IEEE},
	booktitle = {Proceedings of: IEEE Congress on Evolutionary Computation}
}