Computationally Efficient Techniques for Structural Optimization

The objective of this paper is to investigate the efficiency of combinatorial optimization methods and in particular algorithms based on evolution strategies, when incorporated into structural optimization problems. Evolution strategies algorithms are used either on a stand-alone basis, or combined with a conventional mathematical programming technique. Furthermore, the structural analysis phase is replaced by a neural network prediction for the computation of the necessary data for the ES optimization procedure. Advanced domain decomposition techniques is also proposed particularly tailored for parallel solution of large-scale sensitivity analysis problems. Manolis Papadrakakis, Nikos D. Lagaros and Yiannis Tsompanakis.