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Fuzzy Optimization and Decision Making最新文献

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Common probability-based interactive algorithms for group decision making with normalized probability linguistic preference relations 基于归一化概率语言偏好关系的群体决策通用概率交互算法
IF 4.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2021-04-15 DOI: 10.1007/s10700-021-09360-1
Jie Tang, Fanyong Meng, Yongliang Zhang

Probabilistic linguistic variable is a kind of powerful qualitative fuzzy sets, which permits the decision makers (DMs) to apply several linguistic variables with probabilities to denote a judgment. This paper studies group decision making (GDM) with normalized probability linguistic preference relations (NPLPRs). To achieve this goal, an acceptably multiplicative consistency based interactive algorithm is provided to derive common probability linguistic preference relations (CPLPRs) from PLPRs, by which a new acceptably multiplicative consistency concept for NPLPRs is defined. When the multiplicative consistency of NPLPRs is unacceptable, models for deriving acceptably multiplicatively consistent NPLPRs are constructed. Then, it studies incomplete NPLPRs (InNPLPRs) and offers a common probability and acceptably multiplicative consistency based interactive algorithm to determine missing judgments. Furthermore, a correlation coefficient between CPLPRs is provided, by which the weights of the DMs are ascertained. Meanwhile, a consensus index based on CPLPRs is defined. When the consensus does not reach the requirement, a model to increase the level of consensus is built that can ensure the adjusted LPRs to meet the multiplicative consistency and consensus requirement. Moreover, an interactive algorithm for GDM with NPLPRs is provided, which can address unacceptably multiplicatively consistent InNPLPRs. Finally, an example about the evaluation of green design schemes for new energy vehicles is provided to indicate the application of the new algorithm and comparative analysis is conducted.

概率语言变量是一种功能强大的定性模糊集,它允许决策者使用几个具有概率的语言变量来表示一个判断。本文研究了归一化概率语言偏好关系下的群体决策问题。为实现这一目标,提出了一种基于可接受乘性一致性的交互算法,从可接受乘性语言偏好关系中推导出共同概率语言偏好关系,并由此定义了一个新的可接受乘性语言偏好关系的一致性概念。当nplpr的乘一致性不可接受时,构建了可接受的乘一致性nplpr的推导模型。然后,研究了不完全nplpr (innplpr),提出了一种基于通用概率和可接受乘法一致性的交互式算法来确定缺失判断。此外,给出了cplpr之间的相关系数,以此确定dm的权重。同时,定义了基于cplpr的一致性指标。当共识不达到要求时,建立了一个提高共识水平的模型,以保证调整后的lpr满足乘法一致性和共识要求。此外,本文还提出了一种具有nplpr的GDM交互算法,该算法可以解决不可接受的乘性一致的inplpr。最后,以新能源汽车绿色设计方案评价为例,说明了新算法的应用,并进行了对比分析。
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引用次数: 5
Selecting products through text reviews: An MCDM method incorporating personalized heuristic judgments in the prospect theory 通过文本评论选择产品:在前景理论中结合个性化启发式判断的MCDM方法
IF 4.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2021-04-15 DOI: 10.1007/s10700-021-09359-8
Meng Zhao, Xinyuan Shen, Huchang Liao, Mingyao Cai

Online reviews have become an increasingly popular information source in consumer’s decision making process. To help consumers make informed decisions, how to select products through online reviews is a valuable research topic. This work deals with a personized product selection problem with review sentiments under probabilistic linguistic circumstances. To this end, we propose a multi-criteria decision making (MCDM) method incorporating personalized heuristic judgments in the prospect theory (PT). We focus on the role of personalized heuristic judgments on review helpfulness in the final decision outcomes. We demonstrate the consistency between the three common heuristic judgments (with respect to review valence, sentiment extremity, and aspiration levels) and the three behavioral principles of the PT. Then, the products are ranked with the probabilistic linguistic term set (PLTS) input, based on the proposed adjustable PT framework, in which the coefficients of negativity bias are derived from the consumer’s heuristic judgments. Finally, a real case on TripAdvisor.com and two simulation experiments are given to illustrate the validity of the proposed method.

在线评论已经成为消费者决策过程中越来越受欢迎的信息来源。为了帮助消费者做出明智的决定,如何通过在线评论来选择产品是一个有价值的研究课题。本文研究了概率语言环境下带有评论情绪的个性化产品选择问题。为此,我们提出了一种结合前景理论中个性化启发式判断的多准则决策(MCDM)方法。我们关注个性化启发式判断在最终决策结果中对审查有用性的作用。我们证明了三种常见的启发式判断(关于评价、情绪极端和期望水平)与PT的三种行为原则之间的一致性。然后,基于所提出的可调PT框架,使用概率语言术语集(PLTS)输入对产品进行排序,其中负性偏差系数来自消费者的启发式判断。最后,通过TripAdvisor.com的一个实际案例和两个仿真实验验证了所提方法的有效性。
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引用次数: 15
Incremental maintenance of discovered fuzzy association rules 发现的模糊关联规则的增量维护
IF 4.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2021-03-31 DOI: 10.1007/s10700-021-09350-3
Alain Pérez-Alonso, Ignacio J. Blanco, J. Serrano, Luisa M. González-González
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引用次数: 2
Z probabilistic linguistic term sets and its application in multi-attribute group decision making Z概率语言项集及其在多属性群体决策中的应用
IF 4.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2021-03-13 DOI: 10.1007/s10700-021-09351-2
Jiahui Chai, Sidong Xian, Sichong Lu
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引用次数: 13
Option pricing formulas based on uncertain fractional differential equation 基于不确定分数微分方程的期权定价公式
IF 4.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2021-03-05 DOI: 10.1007/s10700-021-09354-z
Weiwei Wang, D. Ralescu
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引用次数: 8
Statistical inference on uncertain nonparametric regression model 不确定非参数回归模型的统计推断
IF 4.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2021-02-17 DOI: 10.1007/s10700-021-09353-0
Jianhua Ding, Zhiqiang Zhang
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引用次数: 17
A structured solution framework for fuzzy minimum spanning tree problem and its variants under different criteria 给出了模糊最小生成树问题及其变体在不同准则下的结构化求解框架
IF 4.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2021-02-15 DOI: 10.1007/s10700-021-09352-1
Ke Wang, Yulin Zhou, Guichao Tian, M. Goh
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引用次数: 1
Two-person cooperative uncertain differential game with transferable payoffs 具有可转移收益的二人合作不确定微分对策
IF 4.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2021-02-13 DOI: 10.1007/s10700-021-09355-y
Yi Zhang, Jinwu Gao, Xiang Li, Xiangfeng Yang
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引用次数: 17
An inverse prospect theory-based algorithm in extended incomplete additive probabilistic linguistic preference relation environment and its application in financial products selection 扩展不完全加性概率语言偏好关系环境下基于逆前景理论的算法及其在金融产品选择中的应用
IF 4.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2020-11-05 DOI: 10.1007/s10700-020-09348-3
N. Liu, Zeshui Xu, Yue He, Xiao-Jun Zeng
{"title":"An inverse prospect theory-based algorithm in extended incomplete additive probabilistic linguistic preference relation environment and its application in financial products selection","authors":"N. Liu, Zeshui Xu, Yue He, Xiao-Jun Zeng","doi":"10.1007/s10700-020-09348-3","DOIUrl":"https://doi.org/10.1007/s10700-020-09348-3","url":null,"abstract":"","PeriodicalId":55131,"journal":{"name":"Fuzzy Optimization and Decision Making","volume":"20 1","pages":"397 - 428"},"PeriodicalIF":4.7,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10700-020-09348-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"52220871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
A novel approach to relative importance ratings of customer requirements in QFD based on probabilistic linguistic preferences 基于概率语言偏好的QFD中客户需求相对重要性评级新方法
IF 4.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2020-10-26 DOI: 10.1007/s10700-020-09347-4
Yinfeng Du, Dun Liu
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引用次数: 11
期刊
Fuzzy Optimization and Decision Making
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