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Relaxed gradient projection algorithm for constrained node-based shape optimization
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DOI：10.1007/s00158-020-02821-y.png)
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Abstract
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In node-based shape optimization, there are a vast amount of design parameters, and the objectives, as well as the physical constraints, are non-linear in state and design. Robust optimization algorithms are required. The methods of feasible directions are widely used in practical optimization problems and know to be quite robust. A subclass of these methods is the gradient projection method. It is an active-set method, it can be used with equality and non-equality constraints, and it has gained significant popularity for its intuitive implementation. One significant issue around efficiency is that the algorithm may suffer from zigzagging behavior while it follows non-linear design boundaries. In this work, we propose a modification to Rosen's gradient projection algorithm. It includes the efficient techniques to damp the zigzagging behavior of the original algorithm while following the non-linear design boundaries, thus improving the performance of the method.
Keywords:
Gradient-based constrained optimization
Shape optimization
Vertex Morphing
Rosen’ s gradient projection algorithm
Node-based shape parametrization
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