Four Hessian-informed trust-region filter variants using low- and high-fidelity surrogates reduce iterations and black-box evaluations by up to an order of magnitude on 25 benchmarks and five engineering cases while lowering tuning sensitivity.
Model-Based Derivative-Free Optimization Methods andSoftware,
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Augments incremental collision laws using the Bouc-Wen model to incorporate external forces as inputs, extends valid parameter ranges, and performs further identification studies on convex viscoplastic body collisions.
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Trust-region filter algorithms utilizing Hessian information for gray-box optimization
Four Hessian-informed trust-region filter variants using low- and high-fidelity surrogates reduce iterations and black-box evaluations by up to an order of magnitude on 25 benchmarks and five engineering cases while lowering tuning sensitivity.
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Incremental Collision Laws Based on the Bouc-Wen Model: Improved Collision Models and Further Results
Augments incremental collision laws using the Bouc-Wen model to incorporate external forces as inputs, extends valid parameter ranges, and performs further identification studies on convex viscoplastic body collisions.