Decision Analysis Linguistic Framework

Everyday human beings are faced with situations they should choose among different alternatives by means of reasoning and mental processes when solving a problem. Many of these decision problems are under uncertain environments including vague, imprecise and subjective information that is usually modeled by linguistic information due to the use of natural language and its relation to mental reasoning processes of the experts when expressing their judgments. In a decision process multiple criteria can be evaluated which involving multiple experts with different degrees of knowledge. Such process can be modeled by using Multi-granular Linguistic Information (MGLI) and Computing with Words (CW) processes to solve the related decision problems. Different methodologies and approaches have been proposed to accomplish this process in an accurate and interpretable way. In this paper we propose a useful Decision Analysis Framework to manage this kind of problems by using the Extended Linguistic Hierarchy (ELH), 2-tuples linguistic representation model and its computational method. The developed Framework has many advantages when dealing with a complex problem in a simple way and its capability of having easy and useful reasonably results.Sociedad Argentina de Informática e Investigación Operativ

A multi-granular linguistic model to evaluate the suitability of installing an ERP system

The use of Enterprise Resource Planning (ERP) has shown clearly useful and economically profitable in most very large organizations which manage a great deal of data in their information systems. Nevertheless, the decision of installing an ERP system is not easy and it depends on the size, future profits and other features of the companies. The assessments of the parameters (features, aspects) used to evaluate the suitability of the ERP may be vague and imprecise because they are usually perceptions of the experts. We propose the use of linguistic information to assess these parameters due to the fact that it is very suitable to model and manage human perceptions. In addition, it may be that each expert has a different knowledge about each parameter and prefers to express his/her preferences in his/her own linguistic term set. Therefore, to manage the evaluation problem of installing an ERP, in this contribution we present a multi-granular linguistic evaluation model that covers these necessities

A linguistic multigranular sensory evaluation model for olive oil

Evaluation is a process that analyzes elements in order to achieve different objectives such as quality inspection, marketing and other fields in industrial companies. This paper focuses on sensory evaluation where the evaluated items are assessed by a panel of experts according to the knowledge acquired via human senses. In these evaluation processes the information provided by the experts implies uncertainty, vagueness and imprecision. The use of the Fuzzy Linguistic Approach 32 has provided successful results modelling such a type of information. In sensory evaluation it may happen that the panel of experts have more or less degree knowledge of about the evaluated items or indicators. So, it seems suitable that each expert could express their preferences in different linguistic term sets based on their own knowledge. In this paper, we present a sensory evaluation model that manages multigranular linguistic evaluation framework based on a decision analysis scheme. This model will be applied to the sensory evaluation process of Olive Oil

Decision Analysis Linguistic Framework

Everyday human beings are faced with situations they should choose among different alternatives by means of reasoning and mental processes when solving a problem. Many of these decision problems are under uncertain environments including vague, imprecise and subjective information that is usually modeled by linguistic information due to the use of natural language and its relation to mental reasoning processes of the experts when expressing their judgments. In a decision process multiple criteria can be evaluated which involving multiple experts with different degrees of knowledge. Such process can be modeled by using Multi-granular Linguistic Information (MGLI) and Computing with Words (CW) processes to solve the related decision problems. Different methodologies and approaches have been proposed to accomplish this process in an accurate and interpretable way. In this paper we propose a useful Decision Analysis Framework to manage this kind of problems by using the Extended Linguistic Hierarchy (ELH), 2-tuples linguistic representation model and its computational method. The developed Framework has many advantages when dealing with a complex problem in a simple way and its capability of having easy and useful reasonably results.Sociedad Argentina de Informática e Investigación Operativ

Profiling clients in the tourism sector using fuzzy linguistic models based on 2-tuples

This work has been funded by the Spanish State Research Agency through the project PID2019-103880RB-I00 / AEI / 10.13039/501100011033.Customer segmentation is a key piece of a company's business strategy. This paper presents a segmentation of the online users of tourism platforms through the recency, frequency and helpfulness of the users. 2-tuples model is applied to these variables to be more precise without loss of information. In addition, the functionality of the proposal made by the authors is verified through a use case in which TripAdvisor opinioners are segmented in reference to the experience lived in hotels and tourist accommodation.Spanish Government PID2019-103880RB-I00 / AEI / 10.13039/50110001103

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

An Interactive Approach Based on Alternative Achievement Scale and Alternative Comprehensive Scale for Multiple Attribute Decision Making under Linguistic Environment

The aim of this paper is to develop an interactive approach for multiple attribute decision making with incomplete weight information under linguistic environment. Some of the concepts are defined, such as the distance between two 2-tuple linguistic variables, the expectation level of alternative, the achievement scale, the alternative comprehensive scale under linguistic environment. Based on these concepts, we establish some linear programming models, through which the decision maker interacts with the analyst. Furthermore, we establish a practical interactive approach for selecting the most desirable alternative(s). The interactive process can be realized by giving and revising the achievement scale and comprehensive scale of alternatives till the achievement scale and the comprehensive scale are achieved to the decision maker’s request. Finally, an illustrative example is also given.The author is very grateful to the associated editor and two anonymous referees for their insightful and constructive comments and suggestions that have led to an improved version of this paper. This work was partly supported by the National Natural Science Foundation of China (No. 90924027, No. 71101043), National Basic Research Program of China (973 Program, No. 2010C B951104), Key Program of National Social Science Foundation of China (No. 10AJY005), College Philosophy and Social Science Research Project of Jiangsu Province under Grant 2011SJD630007.Xu, Y.; Wang, H.; Palacios Marqués, D. (2013). An Interactive Approach Based on Alternative Achievement Scale and Alternative Comprehensive Scale for Multiple Attribute Decision Making under Linguistic Environment. International Journal of Computational Intelligence Systems. 6(1):87-95. https://doi.org/10.1080/18756891.2013.756226S87956

Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence

Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic representations in decision making, we present the taxonomy of existing distributed linguistic representations. Then, we review the key elements and applications of distributed linguistic information processing in decision making, including the distance measurement, aggregation methods, distributed linguistic preference relations, and distributed linguistic multiple attribute decision making models. Next, we provide a discussion on ongoing challenges and future research directions from the perspective of data science and explainable artificial intelligence.National Natural Science Foundation of China (NSFC) 71971039 71421001,71910107002,71771037,71874023 71871149Sichuan University sksyl201705 2018hhs-5