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COMPUTING MULTIPLE SOLUTIONS OF TOPOLOGY OPTIMIZATION PROBLEMS
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DOI：10.1137/20M1326209.png)
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Abstract
En 中文
Topology optimization problems often support multiple local minima due to a lack of convexity. Typically, gradient-based techniques combined with continuation in model parameters are used to promote convergence to more optimal solutions; however, these methods can fail even in the simplest cases. In this paper, we present an algorithm to perform a systematic exploratory search for the solutions of the optimization problem via second order methods without a good initial guess. The algorithm combines the techniques of deflation, barrier methods, and primal-dual active set solvers in a novel way. We demonstrate this approach on several numerical examples, observe mesh independence in certain cases and show that multiple distinct local minima can be recovered.
Keywords:
topology optimization
deflation
barrier methods
second-order methods
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