...
首页> 外文期刊>Soft computing: A fusion of foundations, methodologies and applications >Two regression methods for hesitant multiplicative preference relations with different consistencies
【24h】

Two regression methods for hesitant multiplicative preference relations with different consistencies

机译:两种回归方法,若要与不同常量的若要乘法偏好关系

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Multiplicative preference relation (MPR) is an efficient and widely used tool in describing the preferences of decision makers. The hesitant multiplicative preference relation (HMPR), as an extension of the MPR, is commonly used in collecting and representing all hesitant preferences and judgements of the decision makers. Considering that there usually appear some random or illogical preference degrees in the process of constructing the HMPRs, so it is necessary to derive a pithy preference relation (such as MPR) from the original HMPR through selecting the most proper and abandoning improper preference degrees, at the same time, the derived MPR is with the advantage of both terseness and the best consistency. Based on the multiplicative consistency measure of HMPRs, this paper proposes two regression methods to transform the HMPR into MPRs (called reduced MPRs). With the error analysis, the first proposed regression method provides some steps to not only extract the reduced MPRs from original HMPR but also calculate the consistencies of both the HMPR and the reduced MPRs. A case study reflects that the reduced MPR is with the highest consistency degree among those possible separated MPRs from HMPR. To apply this method to solve practical problems conveniently, a group decision-making procedure with hesitant multiplicative information is further given based on the first regression method. Time complexity comparison between our proposed method and an existing method indicates the effectiveness of our method. In addition, according to the weak consistency, we develop the second regression method and design an algorithm to obtain the reduced MPRs from the HMPR. Furthermore, we provide a method to check the weak consistency of the HMPR and repair the inconsistent one. Numerical examples verify that the second regression method proposed in this paper is an effective technique for checking the weak consistency and modifying the inconsistency HMPR to the one with weak cons
机译:乘法偏好关系(MPR)是描述决策者的偏好的有效和广泛使用的工具。犹豫不决的乘法偏好关系(HMPR)作为MPR的延伸,通常用于收集和代表决策者的所有犹豫偏好和判断。考虑到在构建HMPRS的过程中通常出现一些随机或不合逻辑的偏好度,因此必须通过选择最适当和放弃不正确的偏好度,从而导出从原始HMPR的PITHY偏好关系(例如MPR)同时,派生的MPR是既有特色和最优势的优势。基于HMPRS的乘法一致性测量,本文提出了两种回归方法,将HMPR转化为MPRS(称为减少的MPRS)。通过错误分析,第一个提出的回归方法提供了一些步骤,不仅可以从原始HMPR中提取减少的MPR,而且还计算了HMPR和减少的MPRS的常量。案例研究反映了降低的MPR在HMPR中可能的分离的MPR之间具有最高的一致性程度。为了应用这种方法来方便地解决实际问题,基于第一回归方法进一步提供具有犹豫乘法信息的组决策过程。我们所提出的方法与现有方法之间的时间复杂性比较表明了我们方法的有效性。此外,根据弱的一致性,我们开发了第二个回归方法并设计了一种算法,以获得来自HMPR的减少的MPR。此外,我们提供了一种检查HMPR的弱一致性并修复不一致的方法。数值示例验证本文中提出的第二个回归方法是检查弱一致性并将HMPR修改为具有弱缺点的有效技术

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号