Consensus reaching model with self-confidence-based dynamic weights and personalized adjustment constraints for multi-attribute group decision making

IF 6.5 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Industrial Engineering Pub Date : 2025-03-13 DOI:10.1016/j.cie.2025.111032
Xiaoan Tang , Meng Sun , Qiang Zhang , Witold Pedrycz , Yinghua Shen
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Abstract

It is quite a remarkable fact that experts always hope that the final decision outcome can preserve their original assessments in practical multi-attribute group decision making (MAGDM) activities to a high degree, which can be reflected from their self-confidence in their own assessments. Meanwhile, experts may have different attitude towards the assessment modification at the levels of attribute and alternative in consensus reaching process (CRP), which is commonly characterized by their personalized adjustment constraints on the acceptance of the assessment’ modification suggestions recommended by moderators. Motivated by the facts outlined above, this study proposes a consensus reaching method with self-confidence-based dynamic weights and personalized adjustment constraints for the MAGDM problem. First, a self-confidence-based dynamic weight management method is proposed to accelerate the CRP. Next, considering that experts may have different levels of sensitivities/tolerances for their assessment modifications at the various attribute and alternative levels, a dynamic weight and personalized adjustment constraint-driven consensus model is proposed with the objective of minimizing the distance between experts’ initial assessments and the adjusted collective assessment. Meanwhile, an associated maximum consensus model is implemented to examine whether a predetermined consensus threshold can be achieved with the given assessments. Then, a resolution approach with an interactive CRP that can reconcile the goals that experts should be allocated enough attention and their original assessments should be preserved as much as possible is developed. Finally, three illustrative examples and a comparative study are conducted to show the validity and advantages of the proposal. Overall, this study exhibits three facets of originality: the dynamic weight management method is developed, the personalized assessment-modification willingness is formed, and the interactive consensus reaching algorithm is created.
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基于自信心的动态权重和个性化调整约束的多属性群体决策共识达成模型
在实际的多属性群体决策(MAGDM)活动中,专家们总是高度希望最终的决策结果能够保留他们原来的评价,这是一个值得注意的事实,这可以从他们对自己的评价的自信中体现出来。同时,专家在共识达成过程(CRP)的属性和可选性两个层面对评价修改的态度可能存在差异,这通常表现为他们对主持人推荐的评价修改建议的接受程度存在个性化的调整约束。基于上述事实,本研究提出了一种基于自信的动态权值和个性化调整约束的MAGDM共识达成方法。首先,提出了一种基于自信的动态权重管理方法来加速CRP。其次,考虑到专家在不同属性和备选层面对评估修改的敏感性/容忍度可能不同,提出了以最小化专家初始评估与调整后的集体评估之间的距离为目标的动态权重和个性化调整约束驱动的共识模型。同时,实现了一个相关的最大共识模型,以检验给定的评估是否可以达到预定的共识阈值。然后,开发了一种具有交互式CRP的解决方法,该方法可以协调专家应得到足够重视和应尽可能保留其原始评估的目标。最后,通过三个实例和一个比较研究来说明该建议的有效性和优越性。总体而言,本研究具有三个方面的独创性:开发了动态权重管理方法,形成了个性化的评价修改意愿,创建了交互式共识达成算法。
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来源期刊
Computers & Industrial Engineering
Computers & Industrial Engineering 工程技术-工程:工业
CiteScore
12.70
自引率
12.70%
发文量
794
审稿时长
10.6 months
期刊介绍: Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.
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