Fuzzy Optimization and Decision Making最新文献_第6页

Multilinear target-based decision analysis with hybrid-information targets and performance levels 基于混合信息目标和绩效水平的多线性目标决策分析

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2022-01-30 DOI: 10.1007/s10700-021-09378-5

Xinwei Zhang, Qiong Feng, Shurong Tong, Hakki Eres

引用次数: 1

Cost-allocation problems for fuzzy agents in a fixed-tree network 固定树网络中模糊智能体的成本分配问题

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2022-01-10 DOI: 10.1007/s10700-021-09375-8

Julio R Fernández, I. Gallego, A. Jiménez-Losada, M. Ordóñez

引用次数: 0

Convexity and level sets for interval-valued fuzzy sets 区间值模糊集的凸性与水平集

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2022-01-07 DOI: 10.1007/s10700-021-09376-7

Pedro Huidobro, Pedro Alonso, Vladimír Janiš, S. Montes

引用次数: 4

Finding minimal solutions to the system of addition-min fuzzy relational inequalities 求加法-最小模糊关系不等式组的极小解

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2022-01-05 DOI: 10.1007/s10700-021-09377-6

Yan-Kuen Wu, C. Wen, Yuan-Teng Hsu, Ming-Xian Wang

引用次数: 2

Structure, trend and prospect of operational research: a scientific analysis for publications from 1952 to 2020 included in Web of Science database 运筹学的结构、趋势和前景——对科学网数据库1952年至2020年出版物的科学分析

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2022-01-04 DOI: 10.1007/s10700-021-09380-x

Xinxin Wang, Zeshui Xu, Yong Qin

引用次数: 6

Capacity reliability under uncertainty in transportation networks: an optimization framework and stability assessment methodology 交通网络不确定条件下的容量可靠性:优化框架与稳定性评估方法

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2021-10-25 DOI: 10.1007/s10700-021-09374-9

Hosseini, Ahmad, Pishvaee, Mir Saman

{"title":"Capacity reliability under uncertainty in transportation networks: an optimization framework and stability assessment methodology","authors":"Hosseini, Ahmad, Pishvaee, Mir Saman","doi":"10.1007/s10700-021-09374-9","DOIUrl":"https://doi.org/10.1007/s10700-021-09374-9","url":null,"abstract":"Destruction of the roads and disruption in transportation networks are the aftermath of natural disasters, particularly if they are of great magnitude. As a version of the network capacity reliability problem, this work researches a post-disaster transportation network, where the reliability and operational capacity of links are uncertain. Uncertainty theory is utilized to develop a model of and solve the uncertain maximum capacity path (UMCP) problem to ensure that the maximum amount of relief materials and rescue vehicles arrive at areas impacted by the disaster. We originally present two new problems of (alpha)-maximum capacity path ((alpha)-MCP), which aims to determine paths of highest capacity under a given confidence level ( alpha), and most maximum capacity path (MMCP), where the objective is to maximize the confidence level under a given threshold of capacity value. We utilize these auxiliary programming models to explicate the method to, in an uncertain network, achieve the uncertainty distribution of the MCP value. A novel approach is additionally suggested to confront, in the framework of uncertainty programming, the stability analysis problem. We explicitly enunciate the method of computing the links’ tolerances in ({mathcal{O}}left( m right)) time or ({mathcal{O}}left( {left| {P^{*} } right|m} right)) time (where (m) indicates the number of links in the network and (left| {{text{P}}^{*} } right|) the number of links on the given MCP ({text{P}}^{*})). After all, the practical performance of the method and optimization model is illustrated by adopting two network samples from a real case study to show how our approach works in realistic contexts.","PeriodicalId":55131,"journal":{"name":"Fuzzy Optimization and Decision Making","volume":"21 6","pages":""},"PeriodicalIF":4.7,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138527237","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: 6

Some results for the minimal optimal solution of min-max programming problem with addition-min fuzzy relational inequalities 具有加法的极小模糊关系不等式的极小极大规划问题的极小最优解的一些结果

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2021-10-19 DOI: 10.1007/s10700-021-09371-y

Yan-Kuen Wu, Ching-Feng Wen, Yuan-Teng Hsu, Ming-Xian Wang

引用次数: 1

A graph model for conflict resolution with inconsistent preferences among large-scale participants 大规模参与者偏好不一致时冲突解决的图模型

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2021-10-18 DOI: 10.1007/s10700-021-09373-w

Tang, Ming, Liao, Huchang

{"title":"A graph model for conflict resolution with inconsistent preferences among large-scale participants","authors":"Tang, Ming, Liao, Huchang","doi":"10.1007/s10700-021-09373-w","DOIUrl":"https://doi.org/10.1007/s10700-021-09373-w","url":null,"abstract":"As a flexible and powerful method to resolve strategy conflicts, the graph model for conflict resolution has drawn much attention. In the graph model for conflict resolution, decision-makers need to provide their preference information for all possible scenarios. Most existing studies assumed that decision-makers adopt quantitative representation formats. However, in some real-life situations, decision-makers may tend to use qualitative assessments due to their cognitive expression habits. In addition, stakeholders involved in a graph model can be a group that is composed of a large number of participants. How to manage these participants’ inconsistent preference assessments is also a debatable issue. To fit these gaps, in this study, we propose a graph model for conflict resolution with linguistic preferences, and this model allows participants to use inconsistent assessments. To do this, we first construct a linguistic preference structure, with the necessary concepts being defined. Then, four stability definitions for both a two-decision-maker scenario and an n-decision-maker scenario are introduced. To illustrate the usefulness of the proposed model, an illustrative example regarding the Huawei conflict is provided.","PeriodicalId":55131,"journal":{"name":"Fuzzy Optimization and Decision Making","volume":"11 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2021-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138527236","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: 2

Uncertain seepage equation in fissured porous media 裂隙多孔介质中的不确定渗流方程

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2021-10-16 DOI: 10.1007/s10700-021-09370-z

Lu Yang, Tingqing Ye, Haizhong Yang

引用次数: 3

An innovative unification process for probabilistic hesitant fuzzy elements and its application to decision making 一种创新的概率犹豫模糊元素统一过程及其在决策中的应用

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2021-10-14 DOI: 10.1007/s10700-021-09369-6

B. Farhadinia

引用次数: 3