A dynamic hierarchical quotient topology model based optimal path finding algorithm in complex networks

Optimal path problem has a wide range of examples in production and daily life. However, with the characteristic of dynamics, heterogeneousness, vulnerability and uncertainty, traditional algorithms have some limitations. How to obtain trustworthy path becomes a key issue in the large-scale weighted graph. In this paper, inspired by Bayesian cognitive model and quotient space theory, we propose a novel dynamic hierarchical quotient topology model based optimal path finding algorithm by evaluating the trustworthiness of nodes in complex networks. Theoretical analysis and simulations demonstrate that the proposed algorithm can apparently reduce the ratio of failure path with minor distance and time cost, and efficiently meet the requirement of the optimal path problem in trust.