The application discloses a campus intelligent
nutrition meal system based on deep semantic understanding and
hybrid optimization, relates to the field of intelligent catering
data processing, and comprises a
voucher generation module, a demand purification module, a chain graph construction module and a
hybrid optimization module.The
voucher generation module collects
system data containing associated text and transaction records, separates original intention and actual substitute dishes through a
language model, and generates a will-violating
meal replacement counterfactual
voucher.The demand purification module calculates the amount of money to be credited back, the amount of money to be deducted, and the amount of missing supply to be supplemented according to the voucher and
transaction data, and obtains the purified demand amount by fusion.The chain graph construction module establishes a directed substitution chain
edge based on the voucher, calculates the substitution
equivalent weight, and generates a substitution chain account graph.The
hybrid optimization module establishes constraint conditions and a global objective function based on the purified demand amount and the substitution chain account graph, executes a multi-stage solving logic, and generates an anti-factual
backtracking meal operation instruction.The application effectively corrects the underlying flow data polluted by the will-violating
meal replacement behavior, breaks the supply-demand mismatch chain, and realizes accurate
resource scheduling.