Neural combinatorial optimization (NCO) relies on parallel solution sampling for training, yet existing methods fail to fully exploit the rich information latent in a co-sampled solution group. Preference-optimization methods anchor on the single best solution and discard fine-grained quality and structural signal from...
Yuan-Yu Li, Jin-Tao Xu, Zijiang Liu et al.· 0 citations
This work builds a score-calibrated robustness framework that converts any fixed point predictor into a decision-relevant uncertainty representation through distribution-free conformal calibration, and shows that conformal scores endow fixed black-box predictors with an interpretable uncertainty scale for downstream de...
DualCert introduces constraint-coupled learning, in which current degree equations and dynamically separated subtour-elimination constraints (SECs) define each learned transition, and achieves a mean tour-cost gap of 0.0573%, smaller than the reported NeuroLKH mean gap.
Yancheng Song, Yong-Zhi Qi, Wei Qi et al.· 0 citations
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