# Multi-constrained topology optimization via the topological sensitivity

arXiv: https://arxiv.org/abs/2203.15111 · HTML: https://mlsanity.com/paper/2203.15111/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Mar 2022.

## Built on by (most cited first, 1 of 1)

- [A Generalized Framework for Microstructural Optimization using Neural Networks](https://mlsanity.com/paper/2207.06512/) (2022)

## Abstract (arXiv)

The objective of this paper is to introduce and demonstrate a robust method for multi-constrained topology optimization. The method is derived by combining the topological sensitivity with the classic augmented Lagrangian formulation. The primary advantages of the proposed method are: (1) it rests on well-established augmented Lagrangian formulation for constrained optimization, (2) the augmented topological level-set can be derived systematically for an arbitrary set of loads and constraints, and (3) the level-set can be updated efficiently. The method is illustrated through numerical experiments.