Novel single-valued neutrosophic decision-making approaches based on prospect theory and their applications in physician selection

et al. 2019

Expert Systems

Self Cite

Patients always want a precise diagnosis and appropriate treatment advice when they are diagnosed with a disease. Furthermore, the original information about certain features and symptoms appears in different forms, and the effect of time is always ignored in the process of diagnosis. To overcome these defects, this paper develops a systematic multiperiod hybrid decision support model, which combines the similarity measurement and three‐way decision theory to provide prediction and treatment advice for patients under the fuzzy environment. This multiperiod hybrid decision support model, which considers the effect of time, including transformation module, multiperiod integration module, similarity module, prediction module, and three‐way decision module, provides disease prediction and advice on treatment based on similarities and three‐way decision theory. To validate this model, we construct an illustration composed of four cases, and this ultimately shows that MPH‐SDM can effectively support patients' disease diagnoses and treatment.

Section: Literature Reviewmentioning

confidence: 99%

A multiperiod hybrid decision support model for medical diagnosis and treatment based on similarities and three‐way decision theory

Yan

et al. 2019

Expert Systems

Self Cite

“…e essence of MADM is the process of sorting a limited number of alternatives under given attributes and selecting the optimal one through the evaluation information provided by experts. It has been widely applied in multitudinous aspects [1][2][3][4][5][6][7][8][9]. Owing to the complicacy and nondeterminacy of the decision-making (DM) context, one of the most arduous challenges in course of MADM is how to represent the evaluation information of attributes in fuzzy and uncertain circumstances accurately.…”

Section: Introductionmentioning

confidence: 99%

Hesitant Fuzzy Linguistic Hamy Mean Aggregation Operators and Their Application to Linguistic Multiple Attribute Decision-Making

Run-zhang

Pei

Mathematical Problems in Engineering

2020

Linguistic aggregation operator is a paramount appliance to fix linguistic multiple attribute decision-making (MADM) issues. In the article, the Hamy mean (HM) operator is utilized to fuse hesitant fuzzy linguistic (HFL) information and several novel HFL aggregation operators including the hesitant fuzzy linguistic Hamy mean (HFLHM) operator, weighted hesitant fuzzy linguistic Hamy mean (WHFLHM) operator, hesitant fuzzy linguistic dual Hamy mean (HFLDHM) operator, and weighted hesitant fuzzy linguistic dual Hamy mean (WHFLDHM) operator are proposed. Besides, several paramount theorems and particular cases of these aggregation operators are investigated in detail, and then a novel MADM approach is presented by using the proposed aggregation operators. Ultimately, a practical example is utilized to manifest the effectiveness and practicability of the propounded method.

“…In the real world, a situation in which a person can efficiently offer a judgment of every alternative may be considered an exception rather than the rule. Many studies on multi-criteria decision-making (MCDM) have been conducted [1][2][3][4][5][6][7][8][9][10]. Decision makers (DMs) are typically more confident by simply comparing than explaining or scoring them in the MCDM process.…”

Section: Introductionmentioning

confidence: 99%

Triangular hesitant fuzzy preference relations and their applications in multi-criteria group decision-making

Yan

et al. 2019

Filomat

Self Cite

In this paper, we present a novel multi-criteria decision-making (MCDM) methodology for assessing several alternatives under the triangular hesitant fuzzy environment. A scientific evaluation and prioritization approach is proposed by solving the MCDM problems with triangular hesitant fuzzy preference relations (THFPRs). Firstly, the concepts of THFPRs are defined, and a series of aggregation operators is introduced and their corresponding properties are discussed. Then, we define the consistency of the THFPRs and propose two methods to measure consistency. Furthermore, we construct an MCDM model using THFPR (MCDM-THFPR) to help decision makers assess and prioritise alternatives in the decision making process. Lastly, the validity and feasibility of the proposed MCDM-THFPR method for the MCDM are verified by a comparison with two previous approaches, along with certain discussions. (Junhua Hu) Y Yang et al. / Filomat 33:3 (2019), 917-930 918 progress towards estimating missing preferences in decision-making and proposed a group decisionmaking approach using incomplete reciprocal intuitionistic fuzzy preference relations.However, experts express difficulties in real decision-making problems in terms of their preference degrees for one alternative over others using an exact number. Hesitant fuzzy set (HFS) is a useful tool for solving this issue, and has been developed extensively [30][31][32]. Xia and Xu [33] extended the fuzzy preference relations (FPRs) to hesitant fuzzy preference relations (HFPRs), in which several possible preference values can be considered a hesitant fuzzy number (HFN). Recently, various types of HFPRs, such as hesitant fuzzy linguistic preference relations [34], extended hesitant fuzzy linguistic preference relations [35]; and hesitant-intuitionistic fuzzy preference relations [36], are proposed. Aggregation operators, including hesitant-intuitionistic fuzzy weighted averaging (hesitant-IFWA) operators [36] have also been proposed. Xu and Xia [37] provided distance and similarity measures for HFPRs, and Zhu and Xu [34] suggested consistency measures for hesitant fuzzy linguistic preference relations. Many group decisionmaking methods have also been developed using HFPRs [38,39].The PR consistency, which is its important property, is required to ensure that an approach produces consistent results. Multiplicative and additive consistencies of FPRs [27,40], are strict types of consistency. Experts have proposed many definitions of consistency for FPRs and their extensions; for example, Wang and Xu [35] proposed the consistency measures of PRs in extended hesitant fuzzy linguistic environments. Herrera-Viedma et al. [40] presented a new characterization of the consistency property based on the additive transitivity property of the FPRs. Zhu [41] developed methods for measuring consistency in HFPRs; Zhang et al. [42] discussed consistency in probabilistic linguistic preference relation.HFPRs are effective approaches for decision making that assist DMs in describing their preferences whilst a...