基于差值的软集参数约简方法研究

Research on Difference-based Parameter Reduction Method for Soft Sets

软集理论是一种处理不确定性问题的数学工具,常用于解决决策问题.而决策过程中往往存在着大量的冗余信息,通过参数约简可以删除软集中的冗余信息并保持决策结果不发生改变,从而提高了决策效率.但是现有的正规参数约简(Normal Parameter Reduction)算法由于其严苛的约简条件的限制导致其适用性很低,并且约简结果不能完全反映出所有的冗余信息.针对这些问题,在软集中提出了一种更灵活的参数约简的概念,基于提出的概念,设计出一种基于差值的软集参数约简算法.通过实例说明该算法不仅适用范围广,而且能够删除更多冗余信息,并且保持决策结果不变.

Soft set theory is a mathematical tool for dealing with uncertainty and is often used to solve decision-making problems.In the decision making process,there is often a large amount of redundant information,through the parameter reduction can remove the redundant information in soft sets and keep the decision making results unchanged,thus improving the decision making efficiency.However,the existing normal parameter reduction algorithms have low applicability due to the restriction of the strict reduction conditions,and the reduction results can not completely reflect all the redundant information.To address these problems,a more flexible concept of parameter reduction in soft sets is proposed,and based on the proposed concept,a difference-based parameter reduction algorithm for soft sets is designed.It is illustrated through examples that the algorithm not only has a wide range of application,but also can remove more redundant information and keep the decision making results unchanged.