Reproducible Metaheuristic Scheduling for Adversarial 5G Cognitive-Radio Networks (code and scenarios)

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Code, scenario configurations, and fixed random seeds to reproduce all results (Tables 1–6 and the per-TTI timing figure) in the paper "Reproducible Metaheuristic Scheduling for Adversarial 5G Cognitive-Radio Networks: Genetic-Algorithm Optimization and the Limits of Learned Posture Adaptation." A pure-NumPy simulation of per-TTI 5G/cognitive-radio scheduling under primary-user protection and adversarial jamming, with classical baselines, a genetic-algorithm inner solver, PSO/HHO ablation solvers, a PPO posture controller, and a paired multi-seed statistical harness. See README.md for the reproduce-everything instructions.

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