Supply chain network prescriptions based on artificial intelligence techniques

One or more non-transitory computer-readable storage media, storing instructions which when executed cause one or more processors to execute:

• receiving, by a server computer executing a supply chain network analysis application of a supply chain model, supply chain network data associated with a supply chain network having one or more supply chain nodes;
• programmatically executing inferences on the supply chain network data, by the server computer, using one or more XGBoost path-level machine learning models and one or more heuristic algorithms to implement descriptive analytics, diagnostic analytics, and prescriptive analytics to create and store one or more scenario prescriptions that specify one or more changes to the one or more supply chain nodes, wherein programmatically executing inferences on the supply chain network data comprises:
• extracting one or more data features at a path level, the one or more data features indicating descriptive insights related to one or more paths in the supply chain network;
• identifying, using the one or more XGBoost path-level machine learning models, and via FastTreeShap, one or more cost drivers of the one or more paths in the supply chain network by computing a feature score of each of the one or more data features at the path level;
• creating and storing, using the one or more path-level machine learning models and the feature score of each of the one or more data features, one or more digital representations of the one or more scenario prescriptions;
• and
• executing scenario validation via transmitting a plurality of API calls to one or more networked servers to confirm that nodes exist, that routes exist, and that locations are valid and transmitting one or more database queries to verify that a total time for transiting a scenario is compatible with user or enterprise requirements for transit times;
• generating and displaying one or more visualizations of one or more updated network models that implements the one or more scenario prescriptions;
• and
• communicating updated configuration data to the one or more supply chain nodes.