2-tuple Fuzzy Linguistic Approach Research Articles

A novel solution approach for multiobjective linguistic optimization problems based on the 2-tuple fuzzy linguistic representation model

This paper proposes a novel solution technique for the multi-objective linguistic optimization problems (MOLOPs) based on the 2-tuple fuzzy linguistic approach. The proposed approach has two main advantages. First, it can handle the MOLOPs in which the linguistic information are represented through either monotonic or non-monotonic functions. Second, for both the scenarios, it provides unique solutions in the linguistic form. On the other hand, the existing MOLOP solution approach which is based on the Tsukamoto’s inference method, provides unique solutions only for those MOLOPs in which the linguistic information are expressed as monotonic functions. For the MOLOPs, in which the linguistic information are expressed as non-monotonic functions, the Tsukamoto’s inference method based solution approach cannot provide unique solutions. Moreover, for both monotonic and non-monotonic cases, the Tsukamoto’s inference method based solution approach cannot provide linguistic solutions, but gives only numeric solutions. We have demonstrated the applicability of the proposed MOLOP solution approach considering a case study on student’s performance evaluation, and compared the results with the Tsukamoto’s inference method based solution approach. It is observed that the proposed approach is capable of addressing the limitations of the Tsukamoto’s inference method and hence is more suitable in solving MOLOPs.

A 2-tuple Fuzzy Linguistic Model for Criteria Evaluation on Technological Innovation of Marine Enterprises

Zhang, Q., Liu, S., and Tu, Q., 2019. A 2-tuple fuzzy linguistic representation model for evaluation index selection of technological innovation of marine technology enterprises. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 634–639. Coconut Creek (Florida), ISSN 0749-0208.With the depletion of terrestrial resources, the ocean has become an important resource for the development of countries around the world. As the basic means and supporting force for marine development, marine technology innovation has thus become the main field of national competition. Hence, as the inner motivation and main source of marine technology enterprise development, technological innovation plays an important role in competition. Regarding of the multiple criteria decision-making problem of technological innovation on marine technology enterprises, this paper proposes a method for evaluation index selection by combining 2-tuple fuzzy linguistic approach. Experts evaluate each indicators of the candidate index set and provide the degree of understanding to the index when evaluating the information, which can effectively distinguish the quality of information provided by various experts. Finally, the paper integrates the evaluation information by multiple experts using the aggregated operators based on 2-tuple linguistic model and formed the scientific index system for technological innovation of marine technology enterprises.

Construction of house of quality for new product planning: A 2-tuple fuzzy linguistic approach

A house of quality (HOQ) diagram is used to analyze the critical factors involved in the quality function deployment (QFD) processes for the new product planning (NPP). The principal tasks of the QFD acting process comprise describing and scoring customer requirements (CRs); determining design requirements (DRs), the relationship between CRs and DRs, the correlations among CRs, and the correlations among DRs. Finally, the DRs can be scored by these assessments in NPP. This study proposes various methods of scoring the requirements of current and potential customers to reflect the knowledge and preference differences among different customers regarding CRs. The CR scores provided by different customers can be assessed by using linguistic, numerical, and interval values, or can be assessed using linguistic label sets with different granularity. A 2-tuple fuzzy linguistic computational approach is adopted to aggregate the CR importance scores obtained from customers by using various methods. In addition, to accurately rate the DRs, a modified relationship between CRs and DRs is proposed. The proposed HOQ construction model is practical because it prevents the loss of information during the QFD process for NPP. An example is used to demonstrate the applicability of the proposed model.

Evaluation of the Value Creation in an Innovative Product Using Fuzzy Linguistic Computing

Innovation is a vital tool for growth, enhancing value creation and is also a competitive advantage. The aim of this research is to propose a methodology to evaluate the potential for value creation in innovation of a new product, relatively to intangible and tangible assets. For intangible assets the proposed methodology combines a multiple criteria decision-making method with an adaptation of Tai and Chen (2009) model using 2-tuple fuzzy linguistic approach. This methodology was applied to the EToll product developed by the Portuguese company Brisa Innovation and Technology. It was concluded that the benefits that most contributed to value creation are the development and entrepreneurship of national companies and a better cooperation with suppliers and partners. The EToll also allowed a significant reduction in operating costs in the company. The originality of this study is based in the challenge for business managers to assess the real impact of new products based not only on financial reports, but also in terms of intangible assets and also, how to consider the more appropriate qualitative dimensions to evaluate the performance of intangible assets resulting from innovation.

Crossing the fuzzy front end chasm: Effective product project concept selection using a 2-tuple fuzzy linguistic approach

Many companies focus on how the product concept crosses through the fuzzy front end FFE of the final gate to become a new product development NPD project. Evaluation of product concepts is a gamble in that a wrong decision to enter the product development process may waste time and money. Although analytic hierarchy process AHP and some of its extension methods are widely used for this purpose, their processes consist of pairwise comparisons, meaning that multiple criteria easily confuse judgments and hinder evaluation for decision-makers in practice. Therefore, this study proposes a 2-tuple fuzzy linguistic computing analysis based on fuzzy set theory and multi-criteria decision-making MCDM to solve this problem. The criteria for product concept selection are completely displayed in an evaluation hierarchy from the theoretical perspective. An illustrative example of a product concept evaluation model is used to demonstrate the proposed methodology. The results indicate that it is an effective approach to prioritizing potential NPD projects from a set of feasible product concepts under budget constraints in FFE. In addition, it is feasible to manipulate the evaluation processes by computers, which can reduce the time and mistakes of information translation, and avoid information loss through computing with words.

Evaluating emergency response capacity by fuzzy AHP and 2-tuple fuzzy linguistic approach

Emergency management (EM) is a very important issue with various kinds of emergency events frequently taking place. One of the most important components of EM is to evaluate the emergency response capacity (ERC) of emergency department or emergency alternative. Because of time pressure, lack of experience and data, experts often evaluate the importance and the ratings of qualitative criteria in the form of linguistic variable. This paper presents a hybrid fuzzy method consisting fuzzy AHP and 2-tuple fuzzy linguistic approach to evaluate emergency response capacity. This study has been done in three stages. In the first stage we present a hierarchy of the evaluation index system for emergency response capacity. In the second stage we use fuzzy AHP to analyze the structure of the emergency response capacity evaluation problem. Using linguistic variables, pairwise comparisons for the evaluation criteria and sub-criteria are made to determine the weights of the criteria and sub-criteria. In the third stage, the ratings of sub-criteria are assessed in linguistic values represented by triangular fuzzy numbers to express the qualitative evaluation of experts’ subjective opinions, and the linguistic values are transformed into 2-tuples. Use the 2-tuple linguistic weighted average operator (LWAO) to compute the aggregated ratings of criteria and the overall emergency response capacity (OERC) of the emergency alternative. Finally, we demonstrate the validity and feasibility of the proposed hybrid fuzzy approach by means of comparing the emergency response capacity of three emergency alternatives.

Decision making with extended fuzzy linguistic computing, with applications to new product development and survey analysis

Fuzzy set theory, with its ability to capture and process uncertainties and vagueness inherent in subjective human reasoning, has been under continuous development since its introduction in the 1960s. Recently, the 2-tuple fuzzy linguistic computing has been proposed as a methodology to aggregate fuzzy opinions ( Herrera & Martinez, 2000a, 2000b), for example, in the evaluation of new product development performance ( Wang, 2009) and in customer satisfactory level survey analysis ( Lin & Lee, 2009). The 2-tuple fuzzy linguistic approach has the advantage of avoiding information loss that can potentially occur when combining opinions of experts. Given the fuzzy ratings of the evaluators, the computation procedure used in both Wang (2009) and Lin and Lee (2009) returned a single crisp value as an output, representing the average judgment of those evaluators. In this article, we take an alternative view that the result of aggregating fuzzy ratings should be fuzzy itself, and therefore we further develop the 2-tuple fuzzy linguistic methodology so that its output is a fuzzy number describing the aggregation of opinions. We demonstrate the utility of the extended fuzzy linguistic computing methodology by applying it to two data sets: (i) the evaluation of a new product idea in a Taiwanese electronics manufacturing firm and (ii) the evaluation of the investment benefit of a proposed facility site.

Selecting the Individual Numerical Scale and Prioritization Method in the Analytic Hierarchy Process: A 2-Tuple Fuzzy Linguistic Approach

The validity of the priority vector used in the analytic hierarchy process (AHP) relies on two factors: the selection of a numerical scale and the selection of a prioritization method. The traditional AHP selects only one numerical scale (e.g., the Saaty scale) and one prioritization method (e.g., the eigenvector method) for each particular problem. For this traditional selection approach, there is disagreement on which numerical scale and prioritization method is better in deriving a priority vector. In fact, the best numerical scale and the best prioritization method both rely on the content of the pairwise comparison data provided by the AHP decision makers. By defining a set of concepts regarding the scale function and the linguistic pairwise comparison matrices (LPCMs) of the priority vector and by using LPCMs to unify the format of the input and output of AHP, this paper extends the AHP prioritization process under the 2-tuple fuzzy linguistic model. Based on the extended AHP prioritization process, we present two performance measure criteria to evaluate the effect of the numerical scales and prioritization methods. We also use the performance measure criteria to develop a 2-tuple fuzzy linguistic multicriteria approach to select the best numerical scales and the best prioritization methods for different LPCMs. In this paper, we call this type of selection the individual selection of the numerical scale and prioritization method. We also compare this individual selection with traditional selection by using both random and real data and show better results with individual selection.

A quality evaluation methodology for health-related websites based on a 2-tuple fuzzy linguistic approach

Nowadays, the patients and physicians use the health-related websites as an important information source and, therefore, it is critical the quality evaluation of health- related websites. The quality assessment of health-related websites becomes especially relevant because their use imply the existence of a wide range of threats which can affect people’s health. Additionally, website quality evaluation can also contribute to maximize the exploitation of invested resources by organizations in the development of user-perceived quality websites. But there is not yet a clear and unambiguous definition of the concept of website quality and the debate about quality evaluation on the Web remains open. In this paper, we present a qualitative and user-oriented methodology for assessing quality of health-related websites based on a 2-tuple fuzzy linguistic approach. To identify the quality criteria set, a qualitative research has been carried out using the focus groups technique. The measurement method generates linguistic quality assessments considering the visitors’ judgements with respect to those quality criteria. The combination of the linguistic judgements is implemented without a loss of information by applying a 2-tuple linguistic weighted average operator. This methodology means an improvement on quality evaluation of health websites through the commitment to put users first.

A new evaluation model for intellectual capital based on computing with linguistic variable

In a knowledge era, intellectual capital has become a determinant resource for enterprise to retain and improve competitive advantage. Because the nature of intellectual capital is abstract, intangible, and difficult to measure, it becomes a challenge for business managers to evaluate intellectual capital performance effectively. Recently, several methods have been proposed to assist business managers in evaluating performance of intellectual capital. However, they also face information loss problems while the processes of subjective evaluation integration. Therefore, this paper proposes a suitable model for intellectual capital performance evaluation by combining 2-tuple fuzzy linguistic approach with multiple criteria decision-making (MCDM) method. It is feasible to manipulate the processes of evaluation integration and avoid the information loss effectively. Based on the proposed model, its feasibility is demonstrated by the result of intellectual capital performance evaluation for a high-technology company in Taiwan.

A FUZZY LINGUISTIC IRS MODEL BASED ON A 2-TUPLE FUZZY LINGUISTIC APPROACH

Information Retrieval Systems (IRSs) based on an ordinal fuzzy linguistic approach present some problems of loss of information and lack of precision when working with discrete linguistic expression domains or when applying approximation operations in the symbolic aggregation methods. In this paper, we present a new IRS model based on the 2-tuple fuzzy linguistic approach, which allows us to overcome the problems of ordinal fuzzy linguistic IRSs and improve their performance.

Tuning the matching function for a threshold weighting semantics in a linguistic information retrieval system

Information retrieval is an activity that attempts to produce documents that better fulfill user information needs. To achieve this activity an information retrieval system uses matching functions that specify the degree of relevance of a document with respect to a user query. Assuming linguistic-weighted queries we present a new linguistic matching function for a threshold weighting semantics that is defined using a 2-tuple fuzzy linguistic approach (Herrera F, Martínez L. IEEE Trans Fuzzy Syst 2000;8:746–752). This new 2-tuple linguistic matching function can be interpreted as a tuning of that defined in “Modelling the Retrieval Process for an Information Retrieval System Using an Ordinal Fuzzy Linguistic Approach” (Herrera-Viedma E. J Am Soc Inform Sci Technol 2001;52:460–475). We show that it simplifies the processes of computing in the retrieval activity, avoids the loss of precision in final results, and, consequently, can help to improve the users' satisfaction. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 921–937, 2005.