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Auteurs principaux: Tyburec, Marek, Kočvara, Michal, Handa, Marouan, Zeman, Jan
Format: Preprint
Publié: 2024
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Accès en ligne:https://arxiv.org/abs/2405.08894
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author Tyburec, Marek
Kočvara, Michal
Handa, Marouan
Zeman, Jan
author_facet Tyburec, Marek
Kočvara, Michal
Handa, Marouan
Zeman, Jan
contents Topology optimization of frame structures under free-vibration eigenvalue constraints constitutes a challenging nonconvex polynomial optimization problem with disconnected feasible sets. In this article, we first formulate it as a polynomial semidefinite programming problem (SDP) of minimizing a linear function over a basic semi-algebraic feasible set. We then propose to solve this problem by Lasserre hierarchy of linear semidefinite relaxations providing a sequence of increasing lower bounds. To obtain also a sequence of upper bounds and thus conditions on global $\varepsilon$-optimality, we provide a bilevel reformulation that exhibits a special structure: The lower level is quasiconvex univariate and it has a non-empty interior if the constraints of the upper-level problem are satisfied. After deriving the conditions for the solvability of the lower-level problem, we thus provide a way to construct feasible points to the original SDP. Using such a feasible point, we modify the original nonlinear SDP to satisfy the conditions for the deployment of the Lasserre hierarchy. Solving arbitrary degree relaxation of the hierarchy, we prove that scaled first-order moments associated with the problem variables satisfy feasibility conditions for the lower-level problem and thus provide guaranteed upper and lower bounds on the objective function. Using these bounds, we develop a simple sufficient condition for global $\varepsilon$-optimality and prove that the optimality gap $\varepsilon$ converges to zero if the set of global minimizers is convex. Finally, we illustrate these results with four representative problems for which the hierarchy converges in at most five relaxation degrees
format Preprint
id arxiv_https___arxiv_org_abs_2405_08894
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Global weight optimization of frame structures under free-vibration eigenvalue constraints
Tyburec, Marek
Kočvara, Michal
Handa, Marouan
Zeman, Jan
Optimization and Control
Topology optimization of frame structures under free-vibration eigenvalue constraints constitutes a challenging nonconvex polynomial optimization problem with disconnected feasible sets. In this article, we first formulate it as a polynomial semidefinite programming problem (SDP) of minimizing a linear function over a basic semi-algebraic feasible set. We then propose to solve this problem by Lasserre hierarchy of linear semidefinite relaxations providing a sequence of increasing lower bounds. To obtain also a sequence of upper bounds and thus conditions on global $\varepsilon$-optimality, we provide a bilevel reformulation that exhibits a special structure: The lower level is quasiconvex univariate and it has a non-empty interior if the constraints of the upper-level problem are satisfied. After deriving the conditions for the solvability of the lower-level problem, we thus provide a way to construct feasible points to the original SDP. Using such a feasible point, we modify the original nonlinear SDP to satisfy the conditions for the deployment of the Lasserre hierarchy. Solving arbitrary degree relaxation of the hierarchy, we prove that scaled first-order moments associated with the problem variables satisfy feasibility conditions for the lower-level problem and thus provide guaranteed upper and lower bounds on the objective function. Using these bounds, we develop a simple sufficient condition for global $\varepsilon$-optimality and prove that the optimality gap $\varepsilon$ converges to zero if the set of global minimizers is convex. Finally, we illustrate these results with four representative problems for which the hierarchy converges in at most five relaxation degrees
title Global weight optimization of frame structures under free-vibration eigenvalue constraints
topic Optimization and Control
url https://arxiv.org/abs/2405.08894