New nonlinear formulations for geometric packing problems, solved with FICO Xpress and SCIP, produce improved and first-known solutions for several variants.
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PALM-Mean combines sign-aware piecewise-linear relaxations of locally important kernel terms with closed-form analytic bounds on the rest inside a reduced-space branch-and-bound framework, yielding valid lower bounds and ε-global convergence for GP posterior mean optimization.
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Out-of-the-Box Global Optimization for Packing Problems: New Models and Improved Solutions
New nonlinear formulations for geometric packing problems, solved with FICO Xpress and SCIP, produce improved and first-known solutions for several variants.
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An Efficient Spatial Branch-and-Bound Algorithm for Global Optimization of Gaussian Process Posterior Mean Functions
PALM-Mean combines sign-aware piecewise-linear relaxations of locally important kernel terms with closed-form analytic bounds on the rest inside a reduced-space branch-and-bound framework, yielding valid lower bounds and ε-global convergence for GP posterior mean optimization.