The CARM module boosts neural routing solvers by adaptively modulating embeddings with constraint variables, enabling better use of global observations and improved performance on constrained VRPs.
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A momentum schedule from critical damping speeds convergence and yields an optimizer-invariant diagnostic for locating and correcting specific underperforming layers in trained networks.
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Rethinking Constraint Awareness for Efficient State Embedding of Neural Routing Solver
The CARM module boosts neural routing solvers by adaptively modulating embeddings with constraint variables, enabling better use of global observations and improved performance on constrained VRPs.
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Beta-Scheduling: Momentum from Critical Damping as a Diagnostic and Correction Tool for Neural Network Training
A momentum schedule from critical damping speeds convergence and yields an optimizer-invariant diagnostic for locating and correcting specific underperforming layers in trained networks.