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Term-sparse polynomial optimization for the design of frame structures

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arxiv 2503.20915 v1 pith:RU7ZXNAV submitted 2025-03-26 math.OC

classification math.OC
keywords problemspolynomialcomplianceframemsosoptimizationsolutionsolve
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This work investigates an efficient solution to two fundamental problems in topology optimization of frame structures. The first one involves minimizing structural compliance under linear-elastic equilibrium and weight constraint, while the second one minimizes the weight under compliance constraints. These problems are non-convex and generally challenging to solve globally, with the non-convexity concentrated in a polynomial matrix inequality. We solve these problems using the moment-sum-of-squares (mSOS) hierarchy and improve the scalability by enhancing (mSOS) with the Term Sparsity Pattern (TSP) technique. Additionally, we exploit the unique polynomial structure of our problems by adopting a reduced monomial basis containing only non-mixed terms. These modifications significantly enhance computational efficiency. Extensive numerical experiments demonstrate that our approach achieves global solutions for instances twice as large as those previously solved while substantially accelerating the solution process.

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Cited by 1 Pith paper

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  1. Sparse Polynomial Matrix Optimization

    math.OC 2024-11 conditional novelty 7.0 of 10

    New sparse moment-SOS hierarchies for polynomial matrix optimization reduce SDP size, with term sparsity converging to PMI sign symmetry blocks and a counterexample showing correlative sparsity can fail asymptotically.

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