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Uncertain multi-attributes decision making method based on interval number with probability distribution weighted operators and stochastic dominance degree

机译:基于区间数的概率分布加权算子和随机优势度的不确定多属性决策方法

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摘要

In real world decision making problems, real numbers, random numbers, and interval numbers are often used simultaneously to express the attribute values of alternatives. To solve these uncertain multi attribute decision making problems, we propose a definition of interval number with probability distribution (INPD). This definition gives a uniform form, for real numbers, interval numbers, and random numbers. Under certain conditions, an INPD can degrade to one of the three number forms. We then propose three weighted operators that aggregate opinions expressed by INPD. Furthermore, we propose a new stochastic dominance degree (SDD) definition based on the idea of almost stochastic dominance to rank two INPD. The new definition overcomes defects in traditional stochastic dominance methods. It takes all stakeholders' preferences into account and can measure both standard and almost SDDs. For real numbers and interval numbers, results derived from SDD are consistent with traditional methods. On this basis, a method using INPD weighted operators and SDD is proposed to solve uncertain multi-attribute decision making problems. Finally, three numerical examples are given to illustrate the applicability and effectiveness of the proposed method. (C) 2016 Elsevier B.V. All rights reserved.
机译:在现实世界的决策问题中,经常同时使用实数,随机数和区间数来表示替代方案的属性值。为了解决这些不确定的多属性决策问题,我们提出了一种带概率分布的区间数定义(INPD)。此定义为实数,区间数和随机数给出统一的形式。在某些条件下,INDP可以降级为三种数字形式之一。然后,我们提出三个加权运算符,它们汇总了INPD表示的观点。此外,我们提出了一个新的随机优势度(SDD)定义,该概念基于几乎随机优势将两个INPD排名。新定义克服了传统随机支配方法中的缺陷。它考虑了所有利益相关者的偏好,并且可以衡量标准和几乎SDD。对于实数和区间数,从SDD得出的结果与传统方法一致。在此基础上,提出了一种使用INPD加权算子和SDD的方法来解决不确定的多属性决策问题。最后,给出了三个数值例子,说明了该方法的适用性和有效性。 (C)2016 Elsevier B.V.保留所有权利。

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