Global optimality in minimum compliance topology optimization of frames and shells by moment-sum-of-squares hierarchy

TL;DR

This paper introduces a method using moment-sum-of-squares hierarchy to compute guaranteed globally optimal solutions for minimum compliance topology optimization of frames and shells, overcoming non-convexity challenges.

Contribution

It develops a novel semidefinite programming approach that guarantees global optimality and convergence for complex structural topology optimization problems.

Findings

Hierarchy converges in a small number of steps

Method guarantees global optimality under certain conditions

Provides a feasible upper bound and $ ext{epsilon}$-optimality condition

Abstract

The design of minimum-compliance bending-resistant structures with continuous cross-section parameters is a challenging task because of its inherent non-convexity. Our contribution develops a strategy that facilitates computing all guaranteed globally optimal solutions for frame and shell structures under multiple load cases and self-weight. To this purpose, we exploit the fact that the stiffness matrix is usually a polynomial function of design variables, allowing us to build an equivalent non-linear semidefinite programming formulation over a semi-algebraic feasible set. This formulation is subsequently solved using the Lasserre moment-sum-of-squares hierarchy, generating a sequence of outer convex approximations that monotonically converges from below to the optimum of the original problem. Globally optimal solutions can subsequently be extracted using the Curto-Fialkow flat extension theorem. Furthermore, we show that a simple correction to the solutions of the relaxed problems establishes a feasible upper bound, thereby deriving a simple sufficient condition of global $\varepsilon$-optimality. When the original problem possesses a unique minimum, we show that this solution is found with a zero optimality gap in the limit. These theoretical findings are illustrated on several examples of topology optimization of frames and shells, for which we observe that the hierarchy converges in a finite (rather small) number of steps.