Edge-enabled quantum-safe real-time vaccine supply chain optimization: a decentralized framework for autonomous decision making

The centralized architectures of global vaccine supply chains pose severe security, latency, and operational efficiency challenges to new threats of quantum computing. The article introduces the initial combined edge-enabled quantum-safe real-time optimization of vaccine supply chain based on multi-access edge computing (MEC), post-quantum cryptography, lightweight machine learning, and blockchain consensus algorithms. The framework uses autonomous decision-making distributed edge nodes, and uses novel algorithms such as hierarchical attention network to resource allocation (HAN-RA), quantum-inspired route optimization (QIRO) and adaptive multi-agent reinforcement learning (AMARL). CRYSTALS-Kyber, CRYSTALS-Dilithium and SPHINCS+ are post-quantum cryptographic protocols that are resistant to both classical and quantum adversaries. The improvements in performance have been verified experimentally: 68.2 percentage latency reduction (245 to 78 ms), 188.2 percentage throughput increase (850 to 2,450 throughput (TPS)), 19.5 percentage increase in security score (82 to 98/100), and any number of nodes can be scaled linearly to 10,000 nodes. The system has a 97.2% temperature breach detection, 94.8% high-demand prediction and 99.97% uptime during nonstop 72-h operations. This quantum-resistant architecture operates to fill key gaps in existing supply chain models, offering a scalable, secure and efficient system to support mission-critical healthcare logistics and developing theoretical bases of next-generation post-quantum distributed computing systems.