An Enhanced Interactive and Multi-criteria Decision-Making (TODIM) Method with Probabilistic Dual Hesitant Fuzzy Sets for Risk Evaluation of Arctic Geopolitics

IF 4.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Cognitive Computation Pub Date : 2023-12-19 DOI:10.1007/s12559-023-10229-1
Chenyang Song, Zeshui Xu, Yixin Zhang
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Abstract

The psychological factors of experts play a special role in the process of decision-making, especially in some situations that experts are not completely rational. Traditional decision-making methods always just focus on the aggregation of positive preference information, which do not take the negative attribute information into account at the same time. The probabilistic dual hesitant fuzzy set (PDHFS) is one of the latest fuzzy sets, which can depict experts’ positive and negative preference information with the corresponding probability at the same time. Therefore, to manage the applications with incomplete rationality and two opposite kinds of uncertain preference information, this paper considers the influence of psychological behavior on decision-making results and introduces an interactive method based on the prospect theory. Taking the advantages of PDHFSs in group decision-making problems, we propose the distance measure of PDHFSs, based on which an improved TODIM (TOmada deDecisão Iterativa Multicritério) method under the probabilistic dual hesitant fuzzy environment is also developed. Meanwhile, we provide the specific implementation process of the proposed method. The proposed improved TODIM is applied to the risk evaluation of Arctic geopolitics. We also make a comparison with the traditional aggregation method of PDHFSs. The difference among alternatives obtained by the proposed TODIM method with prospect theory is much greater than the traditional aggregation methods without prospect theory. This paper highlights the benefits and advantages of the proposed TODIM method that is developed based on the prospect theory and probabilistic dual hesitant fuzzy distance measure.

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用概率双隐含模糊集进行北极地缘政治风险评估的增强型互动和多标准决策(TODIM)方法
专家的心理因素在决策过程中起着特殊的作用,尤其是在某些专家并非完全理性的情况下。传统的决策方法总是只注重正面偏好信息的汇总,而没有同时考虑负面属性信息。概率双犹豫模糊集(PDHFS)是最新的模糊集之一,它可以同时用相应的概率来描述专家的积极和消极偏好信息。因此,为了管理不完全理性和两种相反的不确定偏好信息的应用,本文考虑了心理行为对决策结果的影响,并引入了一种基于前景理论的交互方法。利用 PDHFS 在群体决策问题中的优势,我们提出了 PDHFS 的距离度量,并在此基础上开发了概率双犹豫模糊环境下的改进 TODIM(TOmada deDecisão Iterativa Multicritério)方法。同时,我们还提供了所提方法的具体实现过程。提出的改进 TODIM 被应用于北极地缘政治的风险评估。我们还与传统的 PDHFS 聚合方法进行了比较。与不使用前景理论的传统聚合方法相比,使用包含前景理论的 TODIM 方法得到的备选方案之间的差异要大得多。本文强调了基于前景理论和概率双犹豫模糊距离度量开发的 TODIM 方法的优点和优势。
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来源期刊
Cognitive Computation
Cognitive Computation COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-NEUROSCIENCES
CiteScore
9.30
自引率
3.70%
发文量
116
审稿时长
>12 weeks
期刊介绍: Cognitive Computation is an international, peer-reviewed, interdisciplinary journal that publishes cutting-edge articles describing original basic and applied work involving biologically-inspired computational accounts of all aspects of natural and artificial cognitive systems. It provides a new platform for the dissemination of research, current practices and future trends in the emerging discipline of cognitive computation that bridges the gap between life sciences, social sciences, engineering, physical and mathematical sciences, and humanities.
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