Negation provides a novel perspective for the representation of information. However, current research seldom addresses the issue of negation within the random permutation set theory. Based on the concept of belief reassignment, this paper proposes a method for obtaining the negation of permutation mass function in the of random set theory. The convergence of proposed negation is verified, the trends of uncertainty and dissimilarity after each negation operation are investigated. Furthermore, this paper introduces a negation-based uncertainty measure, and designs a multi-source information fusion approach based on the proposed measure. Numerical examples are used to verify the rationality of proposed method.

否定为信息的表示提供了一种新颖的视角。然而，当前的研究很少解决随机排列集合理论中的否定问题。基于置信重分配的概念，提出了随机集理论中排列质量函数求反的方法。验证了所提出的否定的收敛性，研究了每次否定操作后的不确定性和相异性的趋势。此外，本文引入了基于否定的不确定性测度，并基于所提出的测度设计了多源信息融合方法。数值算例验证了所提方法的合理性。