AI Engine That Reads the News and Rewrites Supply Chain Recovery Plans in Seconds
· Source: bioengineer.org
In short
A new study by Zhitian Zhao of Anyang Normal University, published in Discover Artificial Intelligence, presents a semantic-driven resilience decision engine that converts unstructured disruption reports into executable supply-chain recovery plans within seconds. A domain-adapted Chinese BERT model extracts disruption events (F1 91.0% for entities, 84.6% for relations), while a fuzzy-controlled bat algorithm rewrites recovery strategies covering safety stock, alternative suppliers and route replanning. In three realistic scenarios the engine cut average recovery time by 37.2% and additional cost by 36.1% versus manual decision-making, with an average end-to-end latency of 3.31 seconds.
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Tags: supply chain, resilience, disruption management, NLP, optimization, ERP