A Group Decision-Making Framework with Various Rating Attitudes using Fuzzy Set Theory to Prioritize Design Requirements in Quality Function Deployment

A structured method is called quality function deployment (QFD) that translates the voice of the customer into both of the product and service development. The architecture of QFD is composed of a set of matrices that is often referred to as the house of quality (HOQ). HOQ is regarded as a part of the QFD process. The matrices of HOQ include the importance of customer requirements and the relationship between customer requirements and design requirements collected by the decision-making process of a group of people with ambiguousness and fuzziness. Besides, a group of people make decisions to evaluate fuzzy information with different rating or risk-taking attitudes such as optimistic, neutral, and conservative attitudes. Therefore, a group decision-making framework with various rating attitudes using fuzzy set theory can be used in QFD to identify the importance of each design requirement. Furthermore, a numerical example is solved to show that this group decision-making framework with risk-taking attitudes using fuzzy set theory can be accurately and convincingly applied in QFD for prioritizing design requirements with diverse rating attitudes to help the companies increase customer satisfaction and market share

A new lexicographical approach for ranking fuzzy numbers

In the literature many ranking methods have been proposed for comparing the fuzzy numbers, most of them suffer from plenty of shortcomings such as complex calculations, inconsistency with human intuition. To overcome such shortcomings, a new ranking method is proposed for L-R flat fuzzy numbers which is based on the lexicographical ordering approach. It is shown that proposed ranking method satisfies all the reasonable properties of the ordering fuzzy quantities proposed by Wang & Kerre (Fuzzy Sets and Systems 118(2001) 375-385). Finally a comprehensive comparison is done between the existing ranking methods with the proposed one to demonstrate the effectiveness of the proposed ranking method. Keywords: Ranking method, L-R flat fuzzy number

Permutation based decision making under fuzzy environment using Tabu search

One of the techniques, which are used for Multiple Criteria Decision Making (MCDM) is the permutation. In the classical form of permutation, it is assumed that weights and decision matrix components are crisp. However, when group decision making is under consideration and decision makers could not agree on a crisp value for weights and decision matrix components, fuzzy numbers should be used. In this article, the fuzzy permutation technique for MCDM problems has been explained. The main deficiency of permutation is its big computational time, so a Tabu Search (TS) based algorithm has been proposed to reduce the computational time. A numerical example has illustrated the proposed approach clearly. Then, some benchmark instances extracted from literature are solved by proposed TS. The analyses of the results show the proper performance of the proposed method

Technical importance ratings in fuzzy QFD by integrating fuzzy normalization and fuzzy weighted average

AbstractFuzzy quality function deployment (QFD) has been extensively used for translating customer requirements (CRs) into product design requirements (DRs) in fuzzy environments. Existing approaches, however, for rating technical importance of DRs in fuzzy environments are found problematic, either incorrect or inappropriate. This paper investigates how the technical importance of DRs can be correctly rated in fuzzy environments. A pair of nonlinear programming models and two equivalent pairs of linear programming models are developed, respectively, to rate the technical importance of DRs. The developed models are examined and illustrated with two numerical examples

An Asymmetric Index to Compare Trapezoidal Fuzzy Numbers

In this paper, we present a tool to help reduce the uncertainty presented in the resource selection problem when information is subjective in nature. The candidates and the "ideal" resource required by evaluators are modeled by fuzzy subsets whose elements are trapezoidal fuzzy numbers (TrFN). By modeling with TrFN the subjective variables used to determine the best among a set of resources, one should take into account in the decision-making process, not only their expected value, but also the uncertainty that they reflect. Respecting this condition, for each candidate an asymmetric index evaluates the distance between the TrFNs for each of the variables and the corresponding TrFNs of the "ideal" candidate, consolidating them through a weighted average that lets the decision-maker make the final comparison between the candidates, and the selection of the one best suited. We apply this contribution to the case of the selection of the product that is best suited for a "pilot test" to be carried out in some market segment

Ranking fuzzy numbers using preference ratio: A utility function approach

Ranking fuzzy numbers is one of the most important phases in any decision making process in fuzzy environments. In most cases, we deal with fuzzy numbers in the field of evaluating alternatives with fuzzy information or linguistic variables. This paper investigates ranking fuzzy numbers using the concept of preference ratio, introduces the weakness of this method, and proposes a new approach that overcomes the shortcoming of existing method. The proposed approach which is based on the concept of utility function takes the opinion of DM for ranking fuzzy numbers into account

Investors’ preference order of fuzzy numbers

AbstractNowadays greater and greater realistic financial problems are modeled by using the stochastic programming in the fuzzy environment. Hence, ranking a set of fuzzy numbers that is consistent with the investors’ preference becomes important for modelling a realistic problem. In this paper, we will provide a new ranking procedure that is consistent with the preference of the conservative investors. Our ranking procedure satisfies the axioms of three order relations for the separable fuzzy numbers or the triangle fuzzy numbers. We found that our ranking procedure has a better capability of discriminating the order of two fuzzy numbers. For the LR-type fuzzy numbers, our ranking procedure reduces the computational time substantially

Comparative analysis of MCDM methods for the assessment of sustainable housing affordability

While affordability is traditionally assessed in economic terms, this paper tests a new assessment method that draws closer links with sustainability by considering economic, social and environmental criteria that impact on a household's quality of life. The paper presents an empirical application and comparison of six different multiple criteria decision making (MCDM) approaches for the purpose of assessing sustainable housing affordability.The comparative performance of the weighted product model (WPM), the weighted sum model (WSM), the revised AHP, TOPSIS and COPRAS, is investigated. The purpose of the comparative analysis is to determine how different MCDM methods compare when used for a sustainable housing affordability assessment model. 20 Evaluative criteria and 10 alternative are as in Liverpool, England, were considered. The applicability of different MCDM methods for the focused decision problem was investigated. The paper discusses the similarities in MCDM methods, evaluates their robustness and contrasts the resulting rankings