An LLM acting as real-time controller for SIMP topology optimization parameters outperforms fixed schedules and heuristics, delivering 5.7-18.1% lower compliance on 2D and 3D benchmarks.
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Synthetic simulations show noise hurts needle-in-haystack optimization far more than smooth landscapes with local optima, and prior domain knowledge of noise and structure is needed for effective BO in materials research.
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Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization
An LLM acting as real-time controller for SIMP topology optimization parameters outperforms fixed schedules and heuristics, delivering 5.7-18.1% lower compliance on 2D and 3D benchmarks.
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Multi-Variable Batch Bayesian Optimization in Materials Research: Synthetic Data Analysis of Noise Sensitivity and Problem Landscape Effects
Synthetic simulations show noise hurts needle-in-haystack optimization far more than smooth landscapes with local optima, and prior domain knowledge of noise and structure is needed for effective BO in materials research.