Managing Interacting Criteria: Application to Environmental Evaluation Practices

The need for organizations to evaluate their environmental practices has been recently increasing. This fact has led to the development of many approaches to appraise such practices. In this paper, a novel decision model to evaluate company’s environmental practices is proposed to improve traditional evaluation process in different facets. Firstly, different reviewers’ collectives related to the company’s activity are taken into account in the process to increase company internal efficiency and external legitimacy. Secondly, following the standard ISO 14031, two general categories of environmental performance indicators, management and operational, are considered. Thirdly, since the assumption of independence among environmental indicators is rarely verified in environmental context, an aggregation operator to bear in mind the relationship among such indicators in the evaluation results is proposed. Finally, this new model integrates quantitative and qualitative information with different scales using a multi-granular linguistic model that allows to adapt diverse evaluation scales according to appraisers’ knowledge

Granular computing and optimization model-based method for large-scale group decision-making and its application

In large-scale group decision-making process, some decision makers hesitate among several linguistic terms and cannot compare some alternatives, so they often express evaluation information with incomplete hesitant fuzzy linguistic preference relations. How to obtain suitable large-scale group decision-making results from incomplete preference information is an important and interesting issue to concern about. After analyzing the existing researches, we find that: i) the premise that complete preference relation is perfectly consistent is too strict, ii) deleting all incomplete linguistic preference relations that cannot be fully completed will lose valid assessment information, iii) semantics given by decision makers are greatly possible to be changed during the consistency improving process. In order to solve these issues, this work proposes a novel method based on Granular computing and optimization model for large-scale group decision-making, considering the original consistency of incomplete hesitant fuzzy linguistic preference relation and improving its consistency without changing semantics during the completion process. An illustrative example and simulation experiments demonstrate the rationality and advantages of the proposed method: i) semantics are not changed during the consistency improving process, ii) completion process does not significantly alter the inherent quality of information, iii) complete preference relations are globally consistent, iv) final large-scale group decision-making result is acquired by fusing complete preference relations with different weights

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 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

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

An Overview on Fuzzy Modelling of Complex Linguistic Preferences in Decision Making

This work is partially supported by the Spanish National research project TIN2015-66524-P, Spanish Ministry of Economy and Finance Postdoctoral Training (FPDI-2013-18193) and ERDF.Decision makers involved in complex decision making problems usually provide information about their preferences by eliciting their knowledge with different assessments. Usually, the complexity of these decision problems implies uncertainty that in many occasions has been successfully modelled by means of linguistic information, mainly based on fuzzy based linguistic approaches. However, classically these approaches just allow the elicitation of simple assessments composed by either one label or a modifier with a label. Nevertheless, the necessity of more complex linguistic expressions for eliciting decision makers’ knowledge has led to some extensions of classical approaches that allow the construction of expressions and elicitation of preferences in a closer way to human beings cognitive process. This paper provides an overview of the broadest fuzzy linguistic approaches for modelling complex linguistic preferences together some challenges that future proposals should achieve to improve complex linguistic modelling in decision making.Spanish National research project TIN2015-66524-PSpanish Ministry of Economy and Finance Postdoctoral Training FPDI-2013-18193European Union (EU

On aggregation process in linguistic decision making framework

When solving a problem, human beings must face situations in which they should choose among different alternatives by means of reasoning and mental processes. Many of these decision problems are under uncertain environments including vague, imprecise and subjective information that is usually modeled by fuzzy linguistic approach. This approach uses linguistic information or natural language words and its relation to mental reasoning processes of the experts when expressing their assessments. 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. Once decision makers (experts) provided their opinions, it is necessary to combine all these opinions to obtain a single overall result that can be interpreted. An aggregation operator allows accomplishing this objective calculating a global value in different ways. In this paper we study the use of aggregation operators in multi-criteria decision-making processes comparing them and obtaining conclusions about their use in our framework. Furthermore, we propose a new aggregation operator taking into account the criteria importance to evaluate the alternatives, and then an illustrative example shows its outcomes.WATCC - IV Workshop aspectos teóricos de ciencia de la computaciónRed de Universidades con Carreras en Informática (RedUNCI

On aggregation process in linguistic decision making framework

When solving a problem, human beings must face situations in which they should choose among different alternatives by means of reasoning and mental processes. Many of these decision problems are under uncertain environments including vague, imprecise and subjective information that is usually modeled by fuzzy linguistic approach. This approach uses linguistic information or natural language words and its relation to mental reasoning processes of the experts when expressing their assessments. 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. Once decision makers (experts) provided their opinions, it is necessary to combine all these opinions to obtain a single overall result that can be interpreted. An aggregation operator allows accomplishing this objective calculating a global value in different ways. In this paper we study the use of aggregation operators in multi-criteria decision-making processes comparing them and obtaining conclusions about their use in our framework. Furthermore, we propose a new aggregation operator taking into account the criteria importance to evaluate the alternatives, and then an illustrative example shows its outcomes.WATCC - IV Workshop aspectos teóricos de ciencia de la computaciónRed de Universidades con Carreras en Informática (RedUNCI

Integrating Quality Criteria in a Fuzzy Linguistic Recommender System for Digital Libraries

Recommender systems can be used in an academic environment to assist users in their decision making processes to find relevant information. In the literature we can find proposals based in user’ profile or in item’ profile, however they do not take into account the quality of items. In this work we propose the combination of item’ relevance for a user with its quality in order to generate more profitable and accurate recommendations. The system measures item quality and takes it into account as new factor in the recommendation process. We have developed the system adopting a fuzzy linguistic approach.Projects TIN2010-17876, TIC5299 y TIC-599