Measurements of Consensus in Multi-granular Linguistic Group Decision-making

The reaching of consensus in group decision-making (GDM) problems is a common task in group decision processes. In this contribution, we consider GDM with linguistic information. Different experts may have different levels of knowledge about a problem and, therefore, different linguistic term sets (multi-granular linguistic information) can be used to express their opinions. The aim of this paper is to present different ways of measuring consensus in order to assess the level of agreement between the experts in multi-granular linguistic GDM problems. To make the measurement of consensus in multi-granular GDM problems possible and easier, it is necessary to unify the information assessed in different linguistic term sets into a single one. This is done using fuzzy sets defined on a basic linguistic term set (BLTS). Once the information is uniformed, two types of measurement of consensus are carried out: consensus degrees and proximity measures. The first type assesses the agreement among all the experts' opinions, while the second type is used to find out how far the individual opinions are from the group opinion. The proximity measures can be used by a moderator in the consensus process to suggest to the experts the necessary changes to their opinions in order to be able to obtain the highest degree of consensus possible. Both types of measurements are computed in the three different levels of representation of information: pair of alternatives, alternatives and experts.TIC2002-0334

A bio-inspired reinterpretation of symbiotic human-robot collaboration in assembly processes

The emergence of collaborative robotics allowed humans and robots to work closely together to perform manufacturing activities. By combining their distinctive strengths and abilities, humans and robots can support each other in completing complex tasks. The relationship between humans and robots is frequently described in the literature as symbiotic. However, the concept of symbiosis, originally conceived in natural science, is often oversimplified as the mere exchange of mutual benefits. In practice, the term ‘symbiosis’ encompasses a wide range of nteractions, ranging from relationships with positive impacts to relationships with negative impacts. Understanding the foundation of Human-Robot Symbiosis is crucial for its management. Two are the primary aims of this paper: (i) reinterpreting the collaborative tasks in assembly processes according to the properties of symbiotic elationships; (ii) proposing a novel approach for evaluating assembly tasks based on the bio-inspired features of symbiotic Human-Robot collaborative systems

An architecture based on computing with words to support runtime reconfiguration decisions of service-based systems

Service-based systems (SBSs) need to be reconfigured when there is evidence that the selected Web services configurations no further satisfy the specifications models and, thus the decision-related models will need to be updated accordingly. However, such updates need to be performed at the right pace. On the one hand, if the updates are not quickly enough, the reconfigurations that are required may not be detected due to the obsolescence of the specification models used at runtime, which were specified at design-time. On the other hand, the other extreme is to promote premature reconfiguration decisions that are based on models that may be highly sensitive to environmental fluctuations and which may affect the stability of these systems. To deal with the required trade-offs of this situation, this paper proposes the use of linguistic decision-making (LDM) models to represent specification models of SBSs and a dynamic computing-with-words (CWW) architecture to dynamically assess the models by using a multi-period multi-attribute decision making (MP-MADM) approach. The proposed solution allows systems under dynamic environments to offer improved system stability by better managing the trade-off between the potential obsolescence of the specification models, and the required dynamic sensitivity and update of these model

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

Some views on information fusion and logic based approaches in decision making under uncertainty

Decision making under uncertainty is a key issue in information fusion and logic based reasoning approaches. The aim of this paper is to show noteworthy theoretical and applicational issues in the area of decision making under uncertainty that have been already done and raise new open research related to these topics pointing out promising and challenging research gaps that should be addressed in the coming future in order to improve the resolution of decision making problems under uncertainty

Uncertainty assessment in climate change scenarios: a methodological proposal for management of forest ecosystem services

The work introduces a method to quantify potential impact of climate change on cultural ecosystem services in forests. The technique of Hesitant Fuzzy Linguistic Term Set is applied to face with the uncertainty due to climate change as well as subjective opinion of forest experts. Two forest management scenario (current practices as well as climate change-oriented silviculture) are investigated for different time horizons. Results highlight the increasing uncertainty on climate change impact evaluation related to longer time horizons. Potential losses connected to current cultural ecosystem services provision are quantified from spatial as well as economic viewpoint. The method is tested for an illustrative example in the Tuscany region - central Italy

A Linguistic Multi-Criteria Decision Making Model Applied to the Integration of Education Questionnaires

We present a model made up of linguistic multi-criteria decision making processes to integrate the answers to heterogeneous questionnaires, based on a five-point Likert scale, into a unique form rooted in the widespread course experience questionnaire. The main advantage of having the resulting integrated questionnaire is that it can be incorporated into other course experience questionnaire surveys to make benchmarking among organizations. This model has been applied to integrate heterogeneous educational questionnaires at the University of Granada.European Union (EU) TIN2010-17876Andalusian Excellence Projects TIC-05299 TIC-599