An evaluation methodology for ergonomic design of electronic consumer products based on fuzzy axiomatic design

This article is posted with permission of OCP Science imprint. Copyright @ 2008 Old City Publishing Group.The development life cycle of software and electronic products has been shortened by the growth of rapid prototyping techniques. The evaluation of electronic consumer products should consider hardware and software as well as the ergonomic usability, emotional appeal and aesthetic integrity of the design. This research follows a systematic approach to develop an evaluation methodology for electronic mobile products on ergonomic design. The proposed methodology is based on fuzzy multi attribute decision making and fuzzy axiomatic design realized in three steps; determination of ergonomic attributes for electronic consumer products, determination of a representative set of alternatives, and selection of the best alternative in terms of ergonomic design by utilizing fuzzy axiomatic design. A case study is also provided to support the proposed methodology

Ranking Causes of Road Accident Occurrence Using Extended Interval Type-2 Fuzzy TOPSIS

Over the past century there has been a dramatic increase in the number of road accidents in Malaysia. Hence, it is necessary to create a decision making method which can consider various preferences and criteria in order to identify the main causes of the accidents. This paper proposes an Interval Type-2 Fuzzy Technique for Order Preference by Similarity to Ideal Solution (IT2FTOPSIS) method which provides a comprehensive valuation from experts. This method is developed based on the aggregation of experts’ opinions on preferred causes of road accidents. The extended IT2FTOPSIS employs a linguistic scales of positive and negative Interval Type-2 Trapezoidal Fuzzy Number (IT2TrFN) and hybrid averaging approach (from an ambiguity and type-reduction methods) to formulate a collective decision environment. Three authorised personnel from three Malaysian Government agencies were interviewed where they were asked to rank the causes. The analysis shows that the linguistic scales of positive and negative Interval Type-2 Trapezoidal Fuzzy Number (IT2TrFN) and hybrid averaging approach are effective in measuring the uncertainties in the interviewees’ responses. Thus this paper concludes that the extended IT2FTOPSIS is more aligned with the users’ decisions compared to the earlier IT2FTOPSIS. Keywords: Multiple criteria decision-making; interval type-2 fuzzy set; IT2FTOPSIS; road accident

Interval type-2 fuzzy sets in supplier selection

Selection of an appropriate supplier is a crucial and challenging task in the effective management of a supply chain. This study introduces a model for solving the supplier selection problem using interval type-2 fuzzy sets. Moreover, the influence of the membership function shape on the results obtained from the model has been investigated on a real-world problem instance tackled by Ordoobadi

Interval type-2 hesitant fuzzy set method for improving the service quality of domestic airlines in Turkey

This study investigates the level of service quality of domestic airlines in Turkey travelling between Istanbul and London and compares those airline companies according to a set of predetermined criteria. A practical multi-criteria decision making approach combining hesitant and interval type 2 fuzzy sets is adopted and proposed for assessing the service quality of airline companies. The main finding of this study is that passengers care for service prioritization and personalization for a better flight experience and important differences occur in the service quality among the airline companies. Hence, handling of customer complaints, flight problems and individual attention could provide better insights for improving the service quality

Interval type-2 fuzzy sets in supplier selection

Selection of an appropriate supplier is a crucial and challenging task in the effective management of a supply chain. This study introduces a model for solving the supplier selection problem using interval type-2 fuzzy sets. Moreover, the influence of the membership function shape on the results obtained from the model has been investigated on a real-world problem instance tackled by Ordoobadi

Application of a hybrid MCDM method in construction logistics

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Handling a large number of preferences in a multi-level decision-making process

The complexity of a decision is related to the number of persons that are involved, as well as to the diversity of their preferences based on their knowledge, experience or area of expertise. Consequently, it is a challenge to adequately handle a large number of heterogeneous preferences considering that all the participants are considered to be an important source of information to make better motivated decisions. Addressing this challenge constitutes the main motivation in this dissertation because these days decision makers seem to be increasingly interested in the opinions (or preferences) given by persons around a community (and sometimes around the world) through different sources including social media channels. This PhD study provides a set of tools that helps a decision maker to make better motivated decisions by a proper handling of a large number of preferences, identifying and evaluating relevant preferences and handling multiple perspectives. Herein, by 'preference' is meant a greater interest expressed by an individual for a particular alternative over others; by 'relevant' is meant a variety of preferences which are significant (or important) to a particular person acting as a decision maker; and by 'perspective' is understood a position (e.g., social, technical, financial or environmental) adopted by a decision maker when expressing his/ her preferences or constraints

A fuzzy AHP multi-criteria decision-making approach applied to combined cooling, heating and power production systems

Most of the real-world multi-criteria decision-making (MCDM) problems contain a mixture of quantitative and qualitative criteria; therefore quantitative MCDM methods are inadequate for handling this type of decision problems. In this paper, a MCDM method based on the Fuzzy Sets Theory and on the Analytic Hierarchy Process (AHP) is proposed. This method incorporates a number of perspectives on how to approach the fuzzy MCDM problem, as follows: (1) combining quantitative and qualitative criteria (2) expressing criteria pair-wise comparison in linguistic terms and performance of the alternative on each criterion in linguistic terms or exact values when criterion is qualitative or quantitative, respectively, (3) converting all the assessments into trapezoidal fuzzy numbers, (4) using the difference minimization method to calculate the local weight of criteria, employing the algebraic operations of fuzzy numbers based on the concept of α-cuts, (4) calculating the global weight of criteria and the global performance of each alternative using geometric mean and the weighted sum, respectively, (5) using the centroid method to rank the alternatives. Finally, an illustrative example on evaluation of several combined cooling, heat and power production systems is used to demonstrate the effectiveness of the proposed methodology

A review of fuzzy AHP methods for decision-making with subjective judgements

Analytic Hierarchy Process (AHP) is a broadly applied multi-criteria decision-making method to determine the weights of criteria and priorities of alternatives in a structured manner based on pairwise comparison. As subjective judgments during comparison might be imprecise, fuzzy sets have been combined with AHP. This is referred to as fuzzy AHP or FAHP. An increasing amount of papers are published which describe different ways to derive the weights/priorities from a fuzzy comparison matrix, but seldomly set out the relative benefits of each approach so that the choice of the approach seems arbitrary. A review of various fuzzy AHP techniques is required to guide both academic and industrial experts to choose suitable techniques for a specific practical context. This paper reviews the literature published since 2008 where fuzzy AHP is applied to decision-making problems in industry, particularly the various selection problems. The techniques are categorised by the four aspects of developing a fuzzy AHP model: (i) representation of the relative importance for pairwise comparison, (ii) aggregation of fuzzy sets for group decisions and weights/priorities, (iii) defuzzification of a fuzzy set to a crisp value for final comparison, and (iv) consistency measurement of the judgements. These techniques are discussed in terms of their underlying principles, origins, strengths and weakness. Summary tables and specification charts are provided to guide the selection of suitable techniques. Tips for building a fuzzy AHP model are also included and six open questions are posed for future work