Fuzzy Optimization and Decision Making最新文献_第8页

An analytic solution for multi-period uncertain portfolio selection problem 多周期不确定投资组合问题的解析解

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2021-06-26 DOI: 10.1007/s10700-021-09367-8

Bo Li, Yufei Sun, Kok Lay Teo

{"title":"An analytic solution for multi-period uncertain portfolio selection problem","authors":"Bo Li, Yufei Sun, Kok Lay Teo","doi":"10.1007/s10700-021-09367-8","DOIUrl":"https://doi.org/10.1007/s10700-021-09367-8","url":null,"abstract":"The return rates of risky assets in financial markets are usually assumed as random variables or fuzzy variables. For the ever-changing real asset market, this assumption may not always be satisfactory. Thus, it is sometimes more realistic to take the return rates as uncertain variables. However, for the existing works on multi-period uncertain portfolio selection problems, they do not find analytic optimal solutions. In this paper, we propose a method for deriving an analytic optimal solution to a multi-period uncertain portfolio selection problem. First, a new uncertain risk measure is defined to model the investment risk. Then, we formulate a bi-criteria optimization model, where the investment return is maximized, while the investment risk is minimized. On this basis, an equivalent transformation is presented to convert the uncertain bi-criteria optimization problem into an equivalent bi-criteria optimization problem. Then, by applying dynamic programming method, an analytic optimal solution is obtained. Finally, a numerical simulation is carried out to show that the proposed model is realistic and the method being developed is applicable and effective.","PeriodicalId":55131,"journal":{"name":"Fuzzy Optimization and Decision Making","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138527216","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

Editor’s message 编辑的信息

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2021-04-29 DOI: 10.1007/s10700-021-09362-z

Shu-Cherng Fang

引用次数: 0

The DEMATEL–COPRAS hybrid method under probabilistic linguistic environment and its application in Third Party Logistics provider selection 概率语言环境下的DEMATEL-COPRAS混合方法及其在第三方物流供应商选择中的应用

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2021-04-26 DOI: 10.1007/s10700-021-09358-9

Yayi Yuan, Zeshui Xu, Yixin Zhang

{"title":"The DEMATEL–COPRAS hybrid method under probabilistic linguistic environment and its application in Third Party Logistics provider selection","authors":"Yayi Yuan, Zeshui Xu, Yixin Zhang","doi":"10.1007/s10700-021-09358-9","DOIUrl":"https://doi.org/10.1007/s10700-021-09358-9","url":null,"abstract":"With the emergence of outsourcing logistics and the rapid development of the e-commerce business, Third Party Logistics (TPL) plays an indispensable role in modern business. In the TPL provider selection process, uncertain information brings more challenges to decision makers. This paper uses probabilistic linguistic term sets (PLTSs) to describe uncertain decision making information. Firstly, we propose an improved Decision Making Trial and Evaluation Laboratory method, which allows a certain relationship between decision criteria and calculates criteria weights in multi-criteria decision making (MCDM) problems. Then, in order to make full use of uncertain TPL provider information and maximize the values of data, the probabilistic linguistic complex proportional assessment method is proposed and applied to solve the MCDM problems under probabilistic linguistic environment, which needs much less computation than other MCDM methods. Finally, an application example of TPL provider selection is presented to demonstrate the proposed method. A comparative analysis is further conducted to validate the effectiveness of the proposed method.","PeriodicalId":55131,"journal":{"name":"Fuzzy Optimization and Decision Making","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2021-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138527235","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: 31

A comparative analysis of probabilistic linguistic preference relations and distributed preference relations for decision making 概率语言偏好关系与分布偏好关系在决策中的比较分析

IF 4.7 2区计算机科学

Fuzzy Optimization and Decision Making Pub Date : 2021-04-20 DOI: 10.1007/s10700-021-09357-w

Min Xue, Chao Fu, Shanlin Yang

{"title":"A comparative analysis of probabilistic linguistic preference relations and distributed preference relations for decision making","authors":"Min Xue, Chao Fu, Shanlin Yang","doi":"10.1007/s10700-021-09357-w","DOIUrl":"https://doi.org/10.1007/s10700-021-09357-w","url":null,"abstract":"When a decision-maker prefers to compare different alternatives in pairs to handle real situations, there are many different expression styles that can be used. Two representative expression styles are the probabilistic linguistic preference relation (PLPR), which originates from the fuzzy linguistic approach and the distributed preference relation (DPR), which originates from the evidential reasoning approach. Although these two expression styles look quite similar, their meanings, operations, and relevant decision making processes are significantly different. This presents the decision-maker with the challenge of selecting either PLPRs or DPRs in different real cases. To address this issue, this paper provides a detailed analysis of the similarities and differences between PLPRs and DPRs. The analysis is conducted from five perspectives, including modeling of decision making problems, handling of uncertainty, consistency between preference relations, information aggregation, and elicitation process. An engineer selection problem for an automobile manufacturing enterprise is investigated to demonstrate how to appropriately select PLPRs or DPRs to model and analyze decision making problems in real situations with consideration for the preferences of decision-makers.","PeriodicalId":55131,"journal":{"name":"Fuzzy Optimization and Decision Making","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2021-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138527226","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

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

Fuzzy Optimization and Decision Making Pub Date : 2021-04-15 DOI: 10.1007/s10700-021-09360-1

Jie Tang, Fanyong Meng, Yongliang Zhang

{"title":"Common probability-based interactive algorithms for group decision making with normalized probability linguistic preference relations","authors":"Jie Tang, Fanyong Meng, Yongliang Zhang","doi":"10.1007/s10700-021-09360-1","DOIUrl":"https://doi.org/10.1007/s10700-021-09360-1","url":null,"abstract":"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.","PeriodicalId":55131,"journal":{"name":"Fuzzy Optimization and Decision Making","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138527227","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: 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

Fuzzy Optimization and Decision Making Pub Date : 2021-04-15 DOI: 10.1007/s10700-021-09359-8

Meng Zhao, Xinyuan Shen, Huchang Liao, Mingyao Cai

{"title":"Selecting products through text reviews: An MCDM method incorporating personalized heuristic judgments in the prospect theory","authors":"Meng Zhao, Xinyuan Shen, Huchang Liao, Mingyao Cai","doi":"10.1007/s10700-021-09359-8","DOIUrl":"https://doi.org/10.1007/s10700-021-09359-8","url":null,"abstract":"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.","PeriodicalId":55131,"journal":{"name":"Fuzzy Optimization and Decision Making","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138542302","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: 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

Fuzzy Optimization and Decision Making Pub Date : 2021-03-31 DOI: 10.1007/s10700-021-09350-3

Alain Pérez-Alonso, Ignacio J. Blanco, J. Serrano, Luisa M. González-González

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

Fuzzy Optimization and Decision Making Pub Date : 2021-03-13 DOI: 10.1007/s10700-021-09351-2

Jiahui Chai, Sidong Xian, Sichong Lu

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

Fuzzy Optimization and Decision Making Pub Date : 2021-03-05 DOI: 10.1007/s10700-021-09354-z

Weiwei Wang, D. Ralescu

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

Fuzzy Optimization and Decision Making Pub Date : 2021-02-17 DOI: 10.1007/s10700-021-09353-0

Jianhua Ding, Zhiqiang Zhang

引用次数: 17