摘要：Today, the first chapter (1) of "Research on Multi-Attribute Group Decision-Making Methods Based on Probabilistic Linguistic Termi
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“颜读（62）：精读博士论文《基于概率语言术语集理论的多属性群决策方法及其应用研究》第一章绪论（1）”
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"Yan Du (62): A close reading of the first chapter (1) of the doctoral dissertation "Research on Multi-Attribute Group Decision-Making Method Based on Probabilistic Language Terminology Set Theory and Its Application"
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今天小编将从思维导图、精读内容、知识补充三个板块为大家带来《基于概率语言术语集理论的多属性群决策方法及其应用研究》第一章绪论（1）的介绍。
Today, the first chapter (1) of "Research on Multi-Attribute Group Decision-Making Methods Based on Probabilistic Linguistic Terminology Set Theory and Their Applications" from three sections: mind map, intensive reading content, and knowledge supplement.
一、思维导图（Mind Mapping）
二、精读内容（Conduct in-depth reading of the material）
（1）研究背景与意义（Research Background and Significance）
1.研究背景（Research Background）
多属性决策（MADM）是现代决策科学的重要组成部分，广泛应用于经济管理、工程评估、军事等领域。由于单个决策者在信息、时间和认知方面存在局限，复杂情境下往往需要群体决策（GDM）。多属性群决策（MAGDM）正是二者交叉的研究方向，旨在通过多专家、多维指标的综合分析实现更科学的方案选择。
Multi-attribute decision making (MADM) is an important component of modern decision science, widely applied in fields such as economic management, engineering evaluation, and military affairs. Due to the limitations of individual decision-makers in terms of information, time, and cognition, group decision-making (GDM) is often required in complex situations. Multi-attribute group decision making (MAGDM) is a research direction at the intersection of these two fields, aiming to achieve more scientific solution selection through comprehensive analysis of multiple experts and multi-dimensional indicators.
现实决策中，评价信息往往模糊或难以量化。Zadeh于1975年提出模糊语言集（FLSs），用“优、良、中、差”等语言代替精确数值。随后又发展出犹豫模糊集（HFSs）、犹豫模糊语言集（HFLTSs）等模型，用以描述决策者的犹豫与模糊性。然而，传统语言模型无法刻画语言术语出现的概率差异。为此，Pang等提出概率语言术语集（PLTSs），其核心思想是用一组“语言值+概率”表达评价倾向，例如“好(0.7),非常好(0.3)”。进一步，Lin等提出概率不确定语言术语集（PULTSs），允许决策者使用区间语言（如[一般,好]）及对应概率表达不确定性。
In real-world decision-making, evaluation information is often vague or difficult to quantify. In 1975, Zadeh proposed Fuzzy Language Sets (FLSs), using terms like "excellent," "good," "average," and "poor" to replace precise numerical values. Subsequently, models such as Hesitant Fuzzy Sets (HFSs) and Hesitant Fuzzy Language Sets (HFLTSs) were developed to describe the hesitation and ambiguity of decision-makers. However, traditional language models cannot characterize the probabilistic differences in the occurrence of linguistic terms. To address this, Pang et al. proposed Probabilistic Language Term Sets (PLTSs), whose core idea is to express evaluation tendencies using a set of "linguistic values + probabilities," such as "good (0.7), very good (0.3)." Furthermore, Lin et al. proposed Probabilistic Uncertainty Language Term Sets (PULTSs), allowing decision-makers to express uncertainty using interval language (such as [average, good]) and corresponding probabilities.
尽管PLTSs与PULTSs在刻画模糊性上更精细，但其在MAGDM中的系统研究仍处于起步阶段，存在两方面不足：权重确定与方案排序方法缺乏系统性；缺乏考虑决策者心理行为的模型。
Although PLTSs and PULTSs are more refined in characterizing fuzziness, their systematic research in MAGDM is still in its early stages and has two shortcomings: the methods for determining weights and ranking alternatives lack systematicity; and there is a lack of models that take into account the psychological behavior of decision-makers.
2.研究意义（Significance of the study）
理论意义：PLTSs与PULTSs扩展了传统模糊语言集的表达能力，可更细腻地反映决策信息的模糊与不确定性；本研究系统构建了基于PLTSs与PULTSs的MAGDM理论框架，并结合信息熵、CRITIC、前景理论等多种方法，丰富了模糊决策与群体决策的理论体系。
Theoretical significance: PLTSs and PULTSs expand the expressive power of traditional fuzzy language sets, and can more delicately reflect the fuzziness and uncertainty of decision information. This study systematically constructs a MAGDM theoretical framework based on PLTSs and PULTSs, and combines information entropy, CRITIC, prospect theory and other methods to enrich the theoretical system of fuzzy decision-making and group decision-making.
现实意义：研究成果可广泛应用于绿色供应商选择、应急管理、电动汽车充电桩选址、网络与工业安全供应商选择等领域；为管理部门提供科学决策工具，提升风险防控与决策质量，具有显著的实践价值。
Practical significance: The research findings can be widely applied to areas such as green supplier selection, emergency management, electric vehicle charging station site selection, and network and industrial security supplier selection; they provide management departments with scientific decision-making tools, improve risk prevention and control and decision-making quality, and have significant practical value.
（2）国内外研究现状（Current Status of Research at Home and Abroad）
1.概率语言术语集研究现状（Current Status of Research on Probabilistic Language Terminology Sets）
重点介绍了PLTSs的逻辑结构、运算规则及其在ELECTRE、TOPSIS、TODIM、VIKOR等决策模型中的扩展应用。强调其在表达专家偏好、处理模糊信息及改进多属性决策精度上的独特优势。
This paper focuses on the logical structure and operational rules of PLTSs, as well as their extended applications in decision models such as ELECTRE, TOPSIS, TODIM, and VIKOR. It emphasizes their unique advantages in expressing expert preferences, handling fuzzy information, and improving the accuracy of multi-attribute decision-making.
2.概率不确定语言术语集研究现状（Current Status of Research on Probability Uncertainty Language Terminology Sets）
主要综述其定义与典型研究成果，如PULTS-EDAS、PULTS-MABAC、PULTS-Taxonomy等模型。指出当前研究仍偏重模型拓展，缺乏系统的比较与统一理论框架。
This review primarily summarizes the definitions and typical research findings of these models, such as PULTS-EDAS, PULTS-MABAC, and PULTS-Taxonomy. It points out that current research still focuses on model expansion and lacks systematic comparison and a unified theoretical framework.
3.多属性决策方法研究现状（Current Status of Research on Multi-Attribute Decision-Making Methods）
综述了TOPSIS、GRA、CODAS、EDAS、MABAC、TODIM等经典方法的思想、应用与演进。特别指出这些方法在模糊环境下的改进趋势（如基于前景理论的TODIM）。
This paper reviews the ideas, applications, and evolution of classic methods such as TOPSIS, GRA, CODAS, EDAS, MABAC, and TODIM. It particularly highlights the improvement trends of these methods in fuzzy environments (such as TODIM based on prospect theory).
三、知识补充（Supplementary knowledge）
后悔理论由Loomes和Sugden（1982）首次提出，用于解释传统期望效用理论无法解释的实际决策行为。他们发现，在现实情境中，人们在做决策时不仅关注结果的“收益”，还会比较所选方案与未选方案之间的结果差异。如果事后发现未选方案更优，个体会体验到一种负面情绪——后悔；反之，则产生喜悦。因此，后悔理论是一种行为决策理论，强调决策者的情感反应与比较心理在决策过程中的作用。后悔理论是一种以情绪与心理比较为核心的行为决策理论，突破了传统期望效用模型的理性假设。它认为决策者在权衡方案时，会预期可能的后悔程度，并倾向于选择“潜在后悔最小”的方案。该理论在多属性群决策、投资风险、应急管理等领域具有广泛应用，为构建更符合人类认知特征的决策模型提供了理论支撑。
Regret theory, first proposed by Loomes and Sugden (1982), is used to explain real-world decision-making behavior that traditional expected utility theory cannot account for. They found that in real-world situations, people not only focus on the "gains" of the outcome when making decisions, but also compare the differences in outcomes between the chosen and unchosen options. If, in hindsight, the unchosen option is found to be better, the individual experiences a negative emotion—regret; conversely, they experience joy. Therefore, regret theory is a behavioral decision-making theory that emphasizes the role of the decision-maker's emotional response and comparative psychology in the decision-making process. Regret theory is a behavioral decision-making theory centered on emotional and psychological comparisons, breaking through the rational assumptions of the traditional expected utility model. It argues that when weighing options, decision-makers anticipate the potential degree of regret and tend to choose the option with the "minimum potential regret." This theory has wide applications in multi-attribute group decision-making, investment risk, and emergency management, providing theoretical support for constructing decision-making models that better align with human cognitive characteristics.
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翻译：Google翻译
参考资料：ChatGPT
参考文献：卫村. 基于概率语言术语集理论的多属性群决策方法及其应用研究[D]. 西南财经大学, 2023.
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