新型小规模装备备件品种确定的犹豫模糊粗糙集决策方法

针对新研装备备件品种确定过程中决策信息“犹豫性”和“模糊性”特点突出、难以运用传统备件品种确定方法进行决策的问题,提出一种基于犹豫模糊粗糙集的备件品种确定方法。利用风险偏好系数对不完备犹豫模糊信息进行数值延拓,为构建不同风险偏好下备件品种确定的犹豫模糊决策信息系统奠定了基础;考虑得分函数和数值延拓边界的综合因素影响给出了改进的包含度计算公式,并基于包含度定义进行了证明;给出了基于改进包含度计算的备件品种决策属性的约简条件和规则获取方法,实现了犹豫模糊决策信息的深度挖掘和有效利用。以某新研装备备件品种确定为例进行了方法验证,研究结果表明：通过该法能够有效处理犹豫模糊决策信息,获取精简实用的备件品种决策规则集,验证了方法的可行性。

Hesitant fuzzy rough set decision-making method for determining spare parts variety of new small-scale equipment

In view of the problem that the "hesitancy" and "modularity" of the decision-making information are prominent in the process of determining the varieties of spare parts for newly developed equipment, and it is difficult to use the traditional method of determining the varieties of spare parts for decision-making, a method of determining spare parts variety based on hesitation fuzzy rough set is proposed. The risk preference coefficient is used to extend the incomplete hesitancy information, which lays a foundation for establishing the hesitancy information system for different risk preference considering the influence of score function and numerical continuation boundary, an improved inclusion degree formula is given and proved based on the definition of inclusion degree. The reduction condition and rule acquisition method of spare parts variety decision attribute based on improved inclusion calculation are given, which realizes the depth mining and effective utilization of hesitancy and decision information. The method of determining the spare parts variety of a newly developed equipment is verified. The results show that this method can deal with hesitancy and decision information effectively, and obtain a simplified and practical decision rule set of spare parts variety, the feasibility of the method is verified.