The present application belongs to the technical field of supply chain decision optimization, and particularly relates to a supply chain evolution game decision optimization method and
system fusing multi-
source data. The present application firstly calculates strategy distribution entropy based on the
strategy selection proportion of each subject, then calculates external disturbance factors based on external environment indexes in the global trusted state data, secondly calculates comprehensive game
state entropy based on the calculation results of strategy distribution entropy and the calculation results of external disturbance factors, and finally sets a game imbalance early warning threshold to pre-judge potential risks based on the calculation results of comprehensive game
state entropy, and automatically generates a regulation and control strategy to intervene in the game process when the early warning is triggered, thereby guaranteeing the stable operation of the supply chain. This progressive calculation method makes the entropy value not only reflect the change of the internal game state, but also perceive the disturbance of the external environment, thereby realizing accurate risk measurement combining internal and external factors, and being more scientific and authentic than single-dimensional entropy value calculation.