Research Of Maximize Influence On Time-chip Logistics Network

Logistics network is a network system. It is formed by the logistics information activities. Logistics network is a network organization established on the basis of computer technology, network technology, electronic technology, communication technology and automation technology.Influence maximization problem is an important research direction in the field of social influence research. Influence maximization model by the greedy algorithm and some other algorithm can find an individual in a network of influential. And the model can verify whether the influential is accurate.This paper analyzes the influence of logistics network maximization problem. Influence maximization model proposed by Kempe set the activation probability between nodes an unified value. Obviously this does not comply with the real situation in the logistics network. In the logistics network, the probability of influence between every two nodes can`t all be the same. To solve this problem, we use affinity clustering method to calculate the probability values influence between nodes, and through the simulation experiment. Influence maximization model proposed by Kempe is diffused in a static network. But logistics network changes all the time. Static network can`t exhibit a logistics network in real time in the real changes. This paper proposes an independent cascade which is based on time-chip network. Compare to a static network, time-chip network can show better the change of the logistics network. When the independent cascade model based upon the time-chip network diffusion, a node has multiple opportunities to influence its neighbor nodes.