REVIEW OF MODELING PREFERENCES FOR DECISION MODELS

A group decision problem is set in environments where there is a common issue to solve, a set of possible options to choose, and a set of individuals who are experts and express their opinions about the set of possible alternatives with the intention to reach a collective decision as the unique solution of the problem in question. The modeling of the preferences of the decision-maker is an essential stage in the construction of models used in the theory of decision, operations research, economics, etc. On decision problems experts use models of representation of preferences that are close to their disciplines or fields of work. The structures of information most commonly used for the representation of the preferences of experts are vectors of utility, orders of preference and preference relations. In decision problems, the expression of preferences domain is the domain of information used by the experts to express their preferences, the main are numerical, linguistic, and intervalar stressing the multi-granular linguistic. This paper is a review of these concepts. Its purpose is to provide a guide of bibliographic references for these concepts, which are briefly discussed in this document

A new decision making model based on Rank Centrality for GDM with fuzzy preference relations

The work of Enrique Herrera Viedma was supported by the Spanish State Research Agency under Project PID2019-103880RB-I00/AEI/10.13039/501100011033.Preference aggregation in Group Decision Making (GDM) is a substantial problem that has received a lot of research attention. Decision problems involving fuzzy preference relations constitute an important class within GDM. Legacy approaches dealing with the latter type of problems can be classified into indirect approaches, which involve deriving a group preference matrix as an intermediate step, and direct approaches, which deduce a group preference ranking based on individual preference rankings. Although the work on indirect approaches has been extensive in the literature, there is still a scarcity of research dealing with the direct approaches. In this paper we present a direct approach towards aggregating several fuzzy preference relations on a set of alternatives into a single weighted ranking of the alternatives. By mapping the pairwise preferences into transitions probabilities, we are able to derive a preference ranking from the stationary distribution of a stochastic matrix. Interestingly, the ranking of the alternatives obtained with our method corresponds to the optimizer of the Maximum Likelihood Estimation of a particular Bradley-Terry-Luce model. Furthermore, we perform a theoretical sensitivity analysis of the proposed method supported by experimental results and illustrate our approach towards GDM with a concrete numerical example. This work opens avenues for solving GDM problems using elements of probability theory, and thus, provides a sound theoretical fundament as well as plausible statistical interpretation for the aggregation of expert opinions in GDM.Spanish State Research Agency PID2019-103880RB-I00/AEI/10.13039/50110001103

Dealing with imprecise information in group multicriteria decisions: a methodology and a GDSS architecture

This paper outlines a distributed GDSS suitable to be used over the Internet, based on the VIP Analysis methodology and software. VIP Analysis incorporates complementary approaches to deal with the aggregation of multicriteria performances by means of an additive value function under imprecise information. This proposed GDSS intends to support a decision panel forming a democratic decision unit, whose members wish to reach a final decision in a choice problem, based on consensus or on some majority rule. Its purpose is not to impose an aggregated model from the individual ones. Rather, the GDSS is designed to reflect to each member the consequences of his/her inputs, confronting them with analogous reflections of the group members' inputs. We propose aggregation procedures to provide a reflection of the group's inputs to each of its members, and an architecture for a GDSS implementing these procedures.http://www.sciencedirect.com/science/article/B6VCT-4B5JR15-7/1/ec69930c867d6cea3058a818f9f33fe

Evaluation of e-learning web sites using fuzzy axiomatic design based approach

High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered

Mathematical Models for the Comparison of Teaching Strategies in Primary School

Starting from the considerations on modern school of some important scholars, which highlight the complexity of the school system, an analytical path is outlined to identify the best strategies by means of a mathematical model. The method followed is the analytical hierarchical one of Saaty that starts from the investigation of the various objectives, criteria and strategies, and indicates procedures to assign qualitative judgments and to transform them into numerical scores. In particular the AHP procedure is applied to find the degree of effectiveness of various strategies for teaching English, in relation to possible contexts that may arise

Ordering based decision making: a survey

Decision making is the crucial step in many real applications such as organization management, financial planning, products evaluation and recommendation. Rational decision making is to select an alternative from a set of different ones which has the best utility (i.e., maximally satisfies given criteria, objectives, or preferences). In many cases, decision making is to order alternatives and select one or a few among the top of the ranking. Orderings provide a natural and effective way for representing indeterminate situations which are pervasive in commonsense reasoning. Ordering based decision making is then to find the suitable method for evaluating candidates or ranking alternatives based on provided ordinal information and criteria, and this in many cases is to rank alternatives based on qualitative ordering information. In this paper, we discuss the importance and research aspects of ordering based decision making, and review the existing ordering based decision making theories and methods along with some future research directions

Risky multi-criteria group decision making on green capacity investment projects based on supply chain

Green capacity investment projects have rapidly emerged involving suppliers, customers, and manufacturing organizations in supply chain systems with environmental challenges. This paper focuses on and identifies both primary strategic and operational elements that will aid managers in evaluating and making risky multi-criteria decisions on green capacity investment projects. We propose a cloud prospect value consensus process consisting of feedback and adjustment mechanisms that provide modification instructions to the corresponding decision makers for a decision matrix based on the cloud model and prospect theory, which considers psychological behavior, disagreements between decision makers, and the ambiguity of linguistic variable assessment across multi-criteria risks. The new model increases the efficiency and accuracy of decision making. To verify the feasibility and validity of the Cloud Prospect Value Consensus Degree based on the Feedback adjustment mechanism, its performance is compared with three state-of-the-art multi-criteria group decision-making methods

Symbolic Computational Models for Intuitionistic Linguistic Information

In \cite{Cuong14, Phong14}, we first introduced the notion of intuitionistic linguistic labels. In this paper, we develop two symbolic computational models for intuitionistic linguistic labels (intuitionistic linguistic information). Various operators are proposed, their properties are also examined. Then, an application in group decision making using intuitionistic linguistic preference relations is discussed

Integrating Multiple Criteria Decision-Making Models Into the Decision Support System Framework for Marketing Decisions

The paper focuses on integrating the multiple criteria decision making (MCDM) models within the decision support system (DSS) framework to encourage greater use of these models. A DSS framework and the criteria used for the choice of a model is discussed. Based on these criteria MCDM models generally used in the marketing field are evaluated. The possibility of using a mixture of MCDM models within the DSS framework is also explored. Following this, the role of the MCDM models in DSS is delineated. It is argued that, within the problem-solving process, the confluence of MCDM models and DSS plays a vital role in developing high-quality solutions