Session Program


  • 10 July 2017
  • 02:00PM - 04:00PM
  • Room: Giardino
  • Chairs: Yucheng Dong and Luís Martínez

DM II: Hesitant Fuzzy Linguistic Decision Making

Abstract - This paper proposes a measure of consensus for group decision making in the hesitant fuzzy linguistic term sets framework. An extension of the set of hesitant fuzzy linguistic term sets is considered to capture differences among discordant assessments. The difference between a pair of disjoint assessments is given by a measure that takes into account the gap between them. The proposed measure of consensus is defined using this extension, and, as a result, we obtain more accurate values, i.e., the new measure is able to distinguish among group consensus levels that were indistinguishable according to existing measures of consensus. An illustrative example is provided to show the potential of the proposed consensus degree, the process of its computation and a comparison with an existing approach based on a similarity among decision makers.
Abstract - We present Teranga Go!, a social network with a linguistic fuzzy model which deals with hesitant information as a practical application of decision making problems. It is defined to help members to select to whom interact based on collective information regarding real interactions with any user. In this way, we provide a tool intended to build trust among members of a sharing economy community given that is a major drawback from online transactions. As a workbench to run the linguistic decision making model, a web site and a mobile application for iOS and Android offer access to a carpooling service named Teranga Go! that seek to foster the mobility of international migration flows from Europe to Africa, based on concepts of collaborative economy and participatory consumption. The novelty of the site is the possibility of using hesitant linguistic expressions to assess a set of qualitative criteria and the use of the community members as the pool of experts. Unlike many multi criteria decision making problems we do not rank alternatives, we just qualify them using the retrieved opinions, which target a given user, and collected over any interaction with this person along the time. Based on Computing with Words methodology where inputs are words and output are also words, we obtain from the model a linguistic value that is used to represent a karma property present in the user profile.
Abstract - The importance of emergency decision making (EDM) has grown up in recent years because of the frequent occurrence of multiple emergency events (EEs) that have caused important social and economic losses. EDM plays a relevant role when it is necessary to mitigate property and lives losses and reducing the negative impacts on the social and environmental development. Real-world EDM problems are usually characterized by complexity, hard time constraints, lack of information and the impact of the psychological behaviors which makes it very challenging task for the decision maker. This characterization shows the need of dealing with different types of uncertainty and the managing of behaviors to face these problems. This contribution proposes a new emergency decision model that first, uses fuzzy linguistic information to model the subjective information elicited by the decision maker under uncertainty and also the modelling of his/her hesitancy for assessing his/her judgements by using hesitant fuzzy linguistic term sets. Second it integrates the decision maker's psychological behavior by using the prospect theory in a fuzzy based environment. Finally, an example of application of the decision model is carried out to show its validity and applicability.
Abstract - This paper aims to study the consensus approach for the decision making problems with hesitant fuzzy linguistic decision matrices. The distance measure is proposed for the hesitant fuzzy linguistic term sets. Then based on the distance among the individual decision matrices, the group consensus level and some other consensus levels are defined for the hesitant fuzzy decision matrices, and the consensus reaching process is introduced. The model gives the adjustment suggestions to make the information provided for the experts as much as possible, and is helpful for the experts to determinate the adjusted elements. Finally, a numerical example is used to illustrate the feasibility and practicability of the proposed consensus model.
Abstract - In decision making dealing with computing with words, the importance of the statement that words mean different things for different people has been highlighted. In this paper, we focus on personalizing numerical scales of linguistic terms in decision making with hesitant fuzzy linguistic preference relations (HFLPRs). First, an average consistency measure for HFLPRs is provided, and then an optimization-based model to personalize individual semantics via numerical scales is presented, aiming at maximizing the average consistency of HFLPRs. Numerical examples are used to illustrate the proposal.