The invention discloses an AI-driven digital economic supply chain optimization method. According to the invention, a novel supply
chain system with active pre-judgment and dynamic
adaptation is constructed. The core breakthrough of the method is that passive risk management is converted into a opportunity creation mechanism, and traditional supply chain decision logic is remodeled by relying on a virtual-real symbiotic intelligent deduction
system. The
generative adversarial network simulates compound crisis scenes such as geographical conflicts and
digital asset transactions in real time, and a
quantum optimization
algorithm and Monte Carlo tree search are combined, so that the
system not only can predict a conduction path of global
chip shortage to a
production line, but also can generate breakthrough solutions such as cross-chain
encryption settlement and redundant node resource securitization. The pre-judgment type deduction mechanism, block chain dynamic scheduling and metabolic resource configuration form a
closed loop, and in response to encrypted currency flash collapse, a decentralized
payment channel can be automatically switched to avoid risks, a
digital asset arbitrage window can be captured through an intelligent contract, and co-evolution of risk resolution and value increment is realized.