基于关联维数和Kolmogorov熵的协同物流网络有序度控制模型

Order degree control model for collaborative logistics network based on correlation dimension and Kolmogorov entropy

考虑到协同物流网络具有的动态开放、组织复杂等特性,在运行过程中易出现随机混沌现象,影响网络有序程度和运行效率,提出了以保障运行时效和服务质量为目标的协同物流网络有序度控制模型.研究表明,该模型通过关联维数和Kolmogorov熵相结合的方法,可以考察不同状态下协同物流网络运行的复杂程度和混沌特征,实现网络的无序预警;同时从变量选择、参数调整和强度变化等方面,验证了可通过缩减物流功能节点、减少物流任务等纠偏措施降低关联维数和K熵值,提升协同物流网络运行的有序控制能力.

Considering the dynamic openness and chaos phenomena in its operation process which organizing complexity of logistic networks, and the random may affect the ordering degree and network efficiency, the paper, taking the reasonable running time and service quality as decision goals, puts forward an orderingdegree control model of collaborative logistics network. The results show this model can effectively identify the operation differences under different conditions of collaborative logistics network by the correlation dimension and Kolmogorov entropy and warn the disorder of the network early. At same time, some corrective measures, such as reducing functional logistics nodes and logistics tasks, can be taken to decrease the values of correlation dimension and Kolmogorov entropy in the perspective of variable selection, parameter adjustment and intensity change, and to promote the orderly control ability of collaborative logistics networks.