Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling

In three linesLearning-assisted hyper-heuristics for Job Shop Scheduling (JSSP). Proposed selector uses regret-normalized rollout labels, contextual KNN uncertainty estimation, and a gate that acts only when predicted gain exceeds uncertainty-adjusted margin. Reduces Random-HH mean RPD by over an order of magnitude on synthetic instances.

Summary generated by Claude — human-verified