关键词: 信任度排序, 最优协调排序, 线性规划, 多属性决策, 匈牙利算法

Abstract: Concerning the trust degree rank question of which attribute weights are unknown and data are multidimensional, a trust degree rank method based on linear programming theory was proposed. Firstly, the proposed method used linear programming model to make sure the trust degree rank ceiling-floor vector of nodes under the condition of one-dimensional data and unknown attribute weights, and then built the optimal coordinating rank model under multidimensional timing, and then converted the model to the classical assignment problem, and used the Hungary algorithm to solve the model, at last the trust degree rank of each node was obtained. The example analysis shows that, when the optimal coordinating rank model distance parameter q takes low value, the extreme data are not sensitive to the model, the proposed model can prevent evaluation error caused by a few mutation data; when q takes high value, the extreme data are sensitive to the model, the proposed model can identify the potential dishonest evaluation objects of a swing trust degree.

Key words: trust degree rank, optimal coordinating rank, linear programming, multiple attribute decision-making, Hungary algorithm