Title: Neural networks for topology optimization,
Abstract: In this research, we propose a deep learning based approach for speeding up
the topology optimization methods. The problem we seek to solve is the layout
problem. The main novelty of this work is to state the problem as an image
segmentation task. We leverage the power of deep learning methods as the
efficient pixel-wise image labeling technique to perform the topology
optimization. We introduce convolutional encoder-decoder architecture and the
overall approach of solving the above-described problem with high performance.
The conducted experiments demonstrate the significant acceleration of the
optimization process. The proposed approach has excellent generalization
properties. We demonstrate the ability of the application of the proposed model
to other problems. The successful results, as well as the drawbacks of the
current method, are discussed.