@inproceedings {pub3098,
	title = {Hybrid Evolutionary Approach for Level Set Topology Optimization},
	author = {Mariusz Bujny AND Nikola Aulig AND Markus Olhofer AND Fabian Duddeck},
	year = {2016},
	month = {July},
	abstract = {Although Topology Optimization is widely used in many industrial applications, it is still in the initial phase of development for highly nonlinear, multimodal and noisy problems, where the analytical sensitivity information is either not available or difficult to obtain. Since for such problems, gradient-based methods cannot be applied, a search for alternative approaches is inevitable. One possibility is a use of Evolutionary Algorithms, which are well-suited for this type of problems, but involve considerable computational costs. In this paper we propose a hybrid evolutionary optimization method using a geometric Level-Set Method for an implicit representation of mechanical structures. The hybrid approach aims for superior global search properties by using gradient approximations that can be obtained from structural state, equivalent state or any known heuristics. In order to evaluate the proposed method, a minimum compliance problem for a standard cantilever beam benchmark case is considered. The results show that the hybridization can be very beneficial in terms of convergence speed and performance of the optimized designs.},
	publisher = {IEEE},
	booktitle = {IEEE Congress on Evolutionary Computation}
}