Group decision making with incomplete reciprocal preference relations based on multiplicative consistency

This paper comprises a new iterative method for multi-person decision making based on multiplicative consistency with incomplete reciprocal preference relations (IRPRs). Additionally, multiplicative transitivity property of reciprocal preference relation (RPR) is used at the first level to estimate the unknown preference values and get the complete preference relation, then it is confirmed to be multiplicative consistent by using transitive closure formula. Following this, expert's weights are evaluated by merging consistency and trust weights. The consistency weights against the experts are evaluated through multiplicative consistency investigation of the preferences given by each expert, while trust weights play the role to measure the level of trust for an expert. The consensus process determines whether the selection procedure should start or not. If it results in negative, the feedback mechanism is used to enhance the consensus degree. At the end, a numerical example is given to demonstrate the efficiency and practicality of the proposed method

Group consensus measurement in MADM with multiple preference formats

An approach is proposed for measuring the group consensus in multiple attribute decision-making (MADM) problems with experts’ various preference information on alternatives. In the approach, multiple decision-makers give their preference information on alternatives in different formats. The uniformities and aggregation process with fuzzy majority method are employed to obtain the social fuzzy preference relation on the alternatives. Accordingly, the ranking values of the alternatives are obtained based on the obtained individual expert’s fuzzy preference relation, and the social one. The group consensus can be measured based on the ranking values of the alternatives that are derived from the individual expert’s preference information and the social one. An example of selecting robots is presented as an illustration

Group decision-making based on heterogeneous preference relations with self-confidence

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Preference relations are very useful to express decision makers’ preferences over alternatives in the process of group decision-making. However, the multiple self-confidence levels are not considered in existing preference relations. In this study, we define the preference relation with self-confidence by taking multiple self-confidence levels into consideration, and we call it the preference relation with self-confidence. Furthermore, we present a two-stage linear programming model for estimating the collective preference vector for the group decision-making based on heterogeneous preference relations with self-confidence. Finally, numerical examples are used to illustrate the two-stage linear programming model, and a comparative analysis is carried out to show how self-confidence levels influence on the group decision-making results

Least-square method to priority of the fuzzy preference relations with incomplete information

AbstractThe priority problem of incomplete preference relations is investigated. Using the transformation relation between multiplicative preference relation and fuzzy preference relation, we develop a least-square model to obtain the collective priority vector of the incomplete preference relations presented by multiple decision makers, with the existence condition of the solution being developed. Meanwhile, we extend this model to the cases of the fuzzy preference relations with complete information presented by multiple decision makers and the fuzzy preference relation with complete information presented by one decision maker. Finally, it is illustrated by a numerical example that the method proposed is feasible and effective

A chi-square method for priority derivation in group decision making with incomplete reciprocal preference relations

This paper proposes a chi-square method (CSM) to obtain a priority vector for group decision making (GDM) problems where decision-makers’ (DMs’) assessment on alternatives is furnished as incomplete reciprocal preference relations with missing values. Relevant theorems and an iterative algorithm about CSM are proposed. Saaty’s consistency ratio concept is adapted to judge whether an incomplete reciprocal preference relation provided by a DM is of acceptable consistency. If its consistency is unacceptable, an algorithm is proposed to repair it until its consistency ratio reaches a satisfactory threshold. The repairing algorithm aims to rectify an inconsistent incomplete reciprocal preference relation to one with acceptable consistency in addition to preserving the initial preference information as much as possible. Finally, four examples are examined to illustrate the applicability and validity of the proposed method, and comparative analyses are provided to show its advantages over existing approaches

Managing Incomplete Preference Relations in Decision Making: A Review and Future Trends

In decision making, situations where all experts are able to efficiently express their preferences over all the available options are the exception rather than the rule. Indeed, the above scenario requires all experts to possess a precise or sufficient level of knowledge of the whole problem to tackle, including the ability to discriminate the degree up to which some options are better than others. These assumptions can be seen unrealistic in many decision making situations, especially those involving a large number of alternatives to choose from and/or conflicting and dynamic sources of information. Some methodologies widely adopted in these situations are to discard or to rate more negatively those experts that provide preferences with missing values. However, incomplete information is not equivalent to low quality information, and consequently these methodologies could lead to biased or even bad solutions since useful information might not being taken properly into account in the decision process. Therefore, alternative approaches to manage incomplete preference relations that estimates the missing information in decision making are desirable and possible. This paper presents and analyses methods and processes developed on this area towards the estimation of missing preferences in decision making, and highlights some areas for future research

Professional decision-making in medicine: Development of a new measure and preliminary evidence of validity

INTRODUCTION: This study developed a new Professional Decision-Making in Medicine Measure that assesses the use of effective decision-making strategies: seek help, manage emotions, recognize consequences and rules, and test assumptions and motives. The aim was to develop a content valid measure and obtain initial evidence for construct validity so that the measure could be used in future research or educational assessment. METHODS: Clinical scenario-based items were developed based on a review of the literature and interviews with physicians. For each item, respondents are tasked with selecting two responses (out of six plausible options) that they would choose in that situation. Three of the six options reflect a decision-making strategy; these responses are scored as correct. Data were collected from a sample of 318 fourth-year medical students in the United States. They completed a 16-item version of the measure (Form A) and measures of social desirability, moral disengagement, and professionalism attitudes. Professionalism ratings from clerkships were also obtained. A sub-group (n = 63) completed a second 16-item measure (Form B) to pilot test the instrument, as two test forms are useful for pre-posttest designs. RESULTS: Scores on the new measure indicated that, on average, participants answered 75% of items correctly. Evidence for construct validity included the lack of correlation between scores on the measure and socially desirable responding, negative correlation with moral disengagement, and modest to low correlations with professionalism attitudes. A positive correlation was observed with a clerkship rating focused on professionalism in peer interactions. CONCLUSIONS: These findings demonstrate modest proficiency in the use of decision-making strategies among fourth-year medical students. Additional research using the Professional Decision-Making Measure should explore scores among physicians in various career stages, and the causes and correlates of scores. Educators could utilize the measure to assess courses that teach decision-making strategies