Method for triangular fuzzy multiple attribute decision making based on two-dimensional density operator method

Aiming at the triangular fuzzy(TF)multi-attribute decision making(MADM)problem with a preference for the distribution density of attribute(DDA),a decision making method with TF number two-dimensional density(TFTD)operator is proposed based on the density operator theory for the decision maker(DM).Firstly,a simple TF vector clustering method is proposed,which considers the feature of TF number and the geometric distance of vectors.Secondly,the least deviation sum of squares method is used in the program model to obtain the density weight vector.Then,two TFTD operators are defined,and the MADM method based on the TFTD operator is proposed.Finally,a numerical example is given to illustrate the superiority of this method,which can not only solve the TF MADM problem with a preference for the DDA but also help the DM make an overall comparison.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

Shared decision making in rural general practices:a qualitative exploration of older rural South Australians'perceived involvement in clinical consultations with doctors

Background:Shared decision-making(SDM)implementation is a priority for Australian health systems,including general practices but it remains complex for specific groups like older rural Australians.We initiated a qualitative study with older rural Australians to explore barriers to and facilitators of SDM in local general practices.Methods:We conducted a patient-oriented research,partnering with older rural Australians,families,and health service providers in research design.Participants who visited general practices were purposively sampled from five small rural towns in South Australia.A semi-structured interview guide was used for interviews and reflexive thematic coding was conducted.Results:Telephone interviews were held with 27 participants.Four themes were identified around older rural adults’involvement in SDM:(1)Understanding of"patient involvement";(2)Positive and negative outcomes;(3)Barriers to SDM;and(4)Facilitators to SDM.Understanding of patient involvement in SDM considerably varied among participants,with some reporting their involvement was contingent on the“opportunity to ask questions”and the“treatment choices”offered to them.Alongside the opportunity for involvement,barriers such as avoidance of cultural care and a lack of continuity of care are new findings.Challenges encountered in SDM implementation also included resource constraints and time limitations in general practices.Rural knowledge of general practitioners and technology integration in consultations were viewed as potential enablers..Conclusion:Adequate resources and well-defined guidelines about the process should accompany the implementation of SDM in rural general practices of South Australia.Innovative strategies by general practitioners promoting health literacy and culturally-tailored communication approaches could increase older rural Australians'involvement in general.

An Effective Prediction Method for Supporting Decision Making in Real Estate Area Selection

Real estate has been a dominant industry in many countries. One problem for real estate companies is determining the most valuable area before starting a new project. Previous studies on this issue mainly focused on market needs and economic prospects, ignoring the impact of natural disasters. We observe that natural disasters are important for real estate area selection because they will introduce considerable losses to real estate enterprises. Following this observation, we first develop a self-defined new indicator named Average Loss Ratio to predict the losses caused by natural disasters in an area. Then, we adopt the existing ARIMA model to predict the Average Loss Ratio of an area. After that, we propose to integrate the TOPSIS model and the Grey Prediction Model to rank the recommendation levels for candidate areas, thereby assisting real estate companies in their decision-making process. We conduct experiments on real datasets to validate our proposal, and the results suggest the effectiveness of the proposed method.

Solution to multiple attribute group decision making problems with two decision makers

A kind of multiple attribute group decision making （MAGDM） problem is discussed from the perspective of statistic decision-making. Firstly, on the basis of the stability theory, a new idea is proposed to solve this kind of problem. Secondly, a con- crete method corresponding to this kind of problem is proposed. The main tool of our research is the technique o~ the jackknife method. The main advantage of the new method is that it can identify and determine the reliability degree of the existed decision making information. Finally, a traffic engineering example is given to show the effectiveness of the new method.

Decision making tools for optimal material selection:A review

The present work reviews different decision making tools(material comparing and choosing tools)used for selecting the best material considering different parameters.In this review work,the authors have tried to address the following important enquiries:1)the engineering applications addressed by the different material choosing and ranking methods;2)the predominantly used decision making tools addressing the optimal material selection for the engineering applications;3)merits and demerits of decision making tools used;4)the dominantly used criteria or objectives considered while selecting a suitable alternative material;5)overview of DEA on material selection field.The authors have surveyed literatures from different regions of the globe and considered literatures since 1988.The present review not only stresses the importance of material selection in the early design stage of the product development but also aids the design and material engineers to apply different decision making tools systematically.

Enabling weakened hedges in linguistic multi-criteria decision making

A semantics-based model is proposed to enable weakened hedges, such as ＂more or less＂ and ＂roughly＂ in the context of linguistic multi-criteria decision making. First, the resemblance relations are defined based on the semantics of terms on the domain. Then, the hedges can be represented after the upper and loose upper approximations of a linguistic term are derived. Accordingly, some compact formulae can be derived for the semantics of linguistic expressions with hedges. Parameters in these formulae are objectively determined according to the semantics of original terms. The proposed model presents a more natural way to express the decision information under uncertainties and its semantics is clear. The proposed model is clarified by solving the problem of evaluation and selection of sustainable innovative energy technologies. Computational results demonstrate that the model can deal with various uncertainties of the problem. Finally, the model is compared with existing techniques and extended to the case when the semantics of terms are represented by trapezoidal fuzzy numbers.

NOVEL GREY DECISION MAKING MODEL AND ITS NUMERICAL SIMULATION

A grey multi-stage decision making method is proposed for a type of grey multi-index decision problems with weighted values completely unknown and attributes as interval grey numbers. Firstly, a method for compar- ing two grey numbers based on probability is developed to calculate weighted values of the attributes. Secondly, the experts＇ evaluation scores for attribute values are presented in terms of internal grey numbers. Finally, a weight solving method for multiple-stages evaluation is proposed. An example analysis verifies the availability of the proposed method. The method provides a new way of thinking for solving grey decision problem.

Hybrid aggregation operator and its application to multiple attribute decision making problems

By combining the advantages of the additive weighted mean (AWM) operator and the ordered weighted averaging (OWA) operator, this paper first presents a hybrid operator for aggregating data information, and then proposes a hybrid aggregation (HA) operator-based method for multiple attribute decision making (MADM) problems. The theoretical analyses and the numerical results show that the HA operator generalizes both the AWM and OWA operators, and reflects the importance of both the given argument and the ordered position of the argument. Thus, the HA operator can reflect better real situations in practical applications. Finally, an illustrative example is given.

Multiple attribute decision making method based on trapezoid fuzzy linguistic variables

The problem of multiple attribute decision making under fuzzy linguistic environments, in which decision makers can only provide their preferences （attribute values）in the form of trapezoid fuzzy linguistic variables（TFLV）, is studied. The formula of the degree of possibility between two TFLVs is defined, and some of its characteristics are studied. Based on the degree of possibility of fuzzy linguistic variables, an approach to ranking the decision alternatives in multiple attribute decision making with TFLV is developed. The trapezoid fuzzy linguistic weighted averaging （TFLWA） operator method is utilized to aggregate the decision information, and then all the alternatives are ranked by comparing the degree of possibility of TFLV. The method can carry out linguistic computation processes easily without loss of linguistic information, and thus makes the decision results reasonable and effective. Finally, the implementation process of the proposed method is illustrated and analyzed by a practical example.

VIKOR Method-An Effective Compromising Ranking Technique for Decision Making

The VIKOR(VlseKriterijumska Optimizacija I Kompromisno Resenje)method,which is a multi-criteria decision-making method,is examined in this paper.The VIKOR method,like other MCDM techniques such as the Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS),is widely used to solve complex decision-making problems in various fields such as engineering,management,and finance.This paper provides an overview of the VIKOR method,including its application areas,advantages,and disadvantages.Besides,in this survey paper,the process steps of the VIKOR method are described,including determining the decision matrix,normalizing the matrix,determining the weights of the criteria,calculating the utility and regret values,calculating the VIKOR index,and finally ranking the alternatives.By providing an overview of the VIKOR method and its process steps,this paper aims to provide a better understanding of the method and its potential application in different decision-making contexts.

Multiple attribute decision making based on different types of linguistic information

Distance measures between exact linguistic variables and between uncertain linguistic variables are introduced respectively. Based on exact linguistic variables and uncertain linguistic variables, the concepts of positive linguistic ideal solution and negative linguistic ideal solution of attribute values are defined. To rank and select alternatives, based on the distance measures of two types of linguistic variables and the linguistic ideal solutions, a method for multiple attribute decision making with different types of linguistic information is proposed, by which all alternatives can be ranked. The method can carry out linguistic computation processes easily without loss of linguistic information, and thus makes the decision result reasonable and effective. Finally, the implementation process of the proposed method is illustrated and analyzed by a numerical example.

PSA-based prostate cancer screening： the role of active surveillance and informed and shared decision making

Since the first publication describing the identification of prostate-specific antigen （PSA） in the 1960s, much progress has been made. The PSA test changed from being initially a monitoring tool to being also used as a diagnostic tool. Over time, the test has been heavily debated due to its lack of sensitivity and specificity. However, up to now the PSA test is still the only biomarker for the detection and monitoring of prostate cancer. PSA-based screening for prostate cancer is associated with a high proportion of unnecessary testing and overdiagnosis with subsequent overtreatment. In the early years of screening for prostate cancer, high rates of uptake were very important. However, over time the opinion on PSA-based screening has shifted towards the notion of informed choice. Nowadays, it is thought to be unethical to screen men without them being aware of the pros and cons of PSA testing, as well as the fact that an informed choice is related to better patient outcomes. Now, as the results of three major screening studies have been presented and the downsides of screening are becoming better understood, informed choice is becoming more relevant.

Generalization of the linguistic aggregation operator and its application in decision making

A generalization of the linguistic aggregation functions （or operators） is presented by using generalized and quasiarithmetic means. Firstly, the linguistic weighted generalized mean （LWGM） and the linguistic generalized ordered weighted averaging （LGOWA） operator are introduced. These aggregation functions use linguistic information and generalized means in the weighted average （WA） and in the ordered weighted averaging （OWA） function. They are very useful for uncertain situations where the available information cannot be assessed with numerical values but it is possible to use linguistic assessments. These aggregation operators generalize a wide range of aggregation operators that use linguistic information such as the linguistic generalized mean （LGM）, the linguistic OWA （LOWA） operator and the linguistic or- dered weighted quadratic averaging （LOWQA） operator. We also introduce a further generalization by using quasi-arithmetic means instead of generalized means obtaining the quasi-LWA and the quasi-LOWA operator. Finally, we develop an application of the new approach where we analyze a decision making problem regarding the selection of strategies.

Rational and Continuous Measurement of the Emotional Decision Making in Visual Recognition of Facial Emotional Expressions with M.A.R.I.E.: First Half

Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: With M.A.R.I.E. enable a rational quantified measurement of Emotional-Visual-Acuity (EVA) of 1) a) an individual observer, b) in a population aged 20 to 70 years old, 2) measure the range and intensity of expressed emotions by 3 Face-Tests, 3) quantify the performance of a sample of 204 observers with hyper normal measures of cognition, “thymia,” (ibid. defined elsewhere) and low levels of anxiety 4) analysis of the 6 primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual-Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Deci-sion-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Finger-print-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.

TOPSIS with Belief Structure for Group Belief Multiple Criteria Decision Making

The technique for order performance by similarity to ideal solution （TOPSIS） is one of the major techniques in dealing with multiple criteria decision making （MCDM） problems, and the belief structure （BS） model has been used successfully for uncertain MCDM with incompleteness, impreciseness or ignorance. In this paper, the TOPSIS method with BS model is proposed to solve group belief MCDM problems. Firstly, the group belief MCDM problem is structured as a belief decision matrix in which the judgments of each decision maker are described as BS models, and then the evidential reasoning approach is used for aggregating the multiple decision makers＇ judgments. Subsequently, the positive and negative ideal belief solutions are defined with the principle of TOPSIS. To measure the separation from ideal solutions, the concept and algorithm of belief distance measure are defined, which can be used for comparing the difference between BS models. Finally, the relative closeness and ranking index are calculated for ranking the alternatives. A numerical example is given to illustrate the proposed method.

Multi-attribute Decision Making Method Based on the Attribute Difference Degree and Its Application in Rice Breeding

[Objective]The aim was to establish a multi-attribute decision making method and introduce its application in rice breeding.[Method]Based on the defined closeness degree among attributes,the difference degrees among attributes were discussed.Furthermore,the weights of attributes were determined based on the difference degrees among the attributes.[Result]A multi-attribute decision making method based on difference degrees among attributes was established,the feasibility of applying it in rice breeding was also analyzed.[Conclusion]This study enriched the methods to determine attribute weights in multi-attribute decision making and provided the necessary theoretical support for selecting rice varieties scientifically and rationally.

Optimization on Decision Making Driven by Digitalization

The content of this paper refers to the global trend of digitalization and its implications on decision making. The question： will digitalization improving decisions in organizations be a relevant topic for all organizations7 Digitalization is currently the key driver for change in business and organizations. Affected is everything, from market structures to customer behaviour over supply chain and production itself. Internal processes have opportunities for a new design, and production and logistics are possible to redesign. This massive game changing opportunity has to be steered by management and hence management decisions are a must while this transition phase; furthermore, decisions will influence this transition but decisions itself are also affected. The paper is based on a theoretical research, analysing different decision models. In the first part of the paper, typical decision models will be discussed; a rational model with first ideas of the neoclassical economists （e.g. Adam Smith or Max Weber） and scientific approaches of Pascal and de Fermat or Bernoulli, mainly focused on agents which maximize their utility. Further developed by von Neumann and Morgenstern （2004）, economic decisions seem to be a strong rational and mathematical process to find utility maximization. This rational model is illustrated on the one hand to explain the traditional way and has a view on the model of homo oeconomicus. On the other hand, a strong emotional influence on decision making is obvious, because human beeings do not follow strict rational rules. In the second part of the paper, digitalization as one part of globalization will be analysed. Digitalization will change completely the business environment and the setup of organizations. New market structures, customer behaviour, and processes will change the entire operations of businesses. Then, the main discussion of the paper, the impacts of digitalization on decision making will show the trend toward the well-known model of homo oeconomicus, which is a common model in economics; but known with a lot of limitations. Automatization of processes will affect the decision process in organizations. This new decision making processes will be mainly automated in the future, hence an algorithm logic is required and enables the model of homo oeconomicus a revival, driven by machines. As a conclusion based on the above mentioned result, automated decisions will improve the result of decisions, because human emotions will not affect the decision making process anymore.

Multi-attribute group decision making algorithm for web services selection based on QoS

To address the problem of web services selection based on quality, an approach of multi-attribute group decision making algorithm is proposed. Based on the Borda social choice function, the group decision making algorithm aggregates the results of multiple methods with different principles which are used to obtain constantly changing quality of service, thus increasing the confidence to select the most appropriate web service for a special task. The experimental results indicate that the proposed approach has better scalability and can be applied to large-scale distributed service computing environments. It is also shown that the proposed group decision making approach can effectively optimize the services selection and outperforms the random and robin policies. By using this approach, it can extend a method to obtain constantly changing quality of service and construct a synthetic information entity with multi-level knowledge, which guarantees the accuracy of services selection.

Aggregation operators on intuitionistic trapezoidal fuzzy number and its application to multi-criteria decision making problems

Intuitionistic trapezoidal fuzzy numbers and their operational laws are defined. Based on these operational laws, some aggregation operators, including intuitionistic trapezoidal fuzzy weighted arithmetic averaging operator and weighted geometric averaging operator are proposed. Expected values, score function, and accuracy function of intuitionitsic trapezoidal fuzzy numbers are defined. Based on these, a kind of intuitionistic trapezoidal fuzzy multi-criteria decision making method is proposed. By using these aggregation operators, criteria values are aggregated and integrated intuitionistic trapezoidal fuzzy numbers of alternatives are attained. By comparing score function and accuracy function values of integrated fuzzy numbers, a ranking of the whole alternative set can be attained. An example is given to show the feasibility and availability of the method.