关键词: 供应链, 协同行为模式, A*算法

Abstract: Owing to the fact that the consideration of linear model used by traditional supply chain solving method was limited,which was not met the requirement of dynamic supply chain network under Internet multi-source big data environment,the dynamic supply chain was mapped into graph model,and a half-instance model detection method based on  collaborative matrix factorization was proposed on this basis,which was applied to detect a half-instantiated cooperative behavior on the dynamic supply chain network.According to a given collaborative behavior pattern,a personalized supply chain candidate set was computed with collaborative matrix factorization;by calculating the closeness degree between entity in supply chain network,a personalized supply chain candidate set was formed with A* algorithm graph search;according to other personalized restrictions such as time and cost,the final supply chain solutions was formed after clipping.Through the experiment of e-commerce supply chain data collection oriented to apparel field,the correctness,efficiency and accuracy of the method was verified.

Key words: supply chains, collaborative behavior patterns, A* algorithm