An improvised similarity measure for generalized fuzzy numbers

Similarity measure between two fuzzy sets is an important tool for comparing various characteristics of the fuzzy sets. It is a preferred approach as compared to distance methods as the defuzzification process in obtaining the distance between fuzzy sets will incur loss of information. Many similarity measures have been introduced but most of them are not capable to discriminate certain type of fuzzy numbers. In this paper, an improvised similarity measure for generalized fuzzy numbers that incorporate several essential features is proposed. The features under consideration are geometric mean averaging, Hausdorff distance, distance between elements, distance between center of gravity and the Jaccard index. The new similarity measure is validated using some benchmark sample sets. The proposed similarity measure is found to be consistent with other existing methods with an advantage of able to solve some discriminant problems that other methods cannot. Analysis of the advantages of the improvised similarity measure is presented and discussed. The proposed similarity measure can be incorporated in decision making procedure with fuzzy environment for ranking purposes

Evaluation of e-learning web sites using fuzzy axiomatic design based approach

High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered

Intuitionistic Fuzzy Time Series Functions Approach for Time Series Forecasting

Fuzzy inference systems have been commonly used for time series forecasting in the literature. Adaptive network fuzzy inference system, fuzzy time series approaches and fuzzy regression functions approaches are popular among fuzzy inference systems. In recent years, intuitionistic fuzzy sets have been preferred in the fuzzy modeling and new fuzzy inference systems have been proposed based on intuitionistic fuzzy sets. In this paper, a new intuitionistic fuzzy regression functions approach is proposed based on intuitionistic fuzzy sets for forecasting purpose. This new inference system is called an intuitionistic fuzzy time series functions approach. The contribution of the paper is proposing a new intuitionistic fuzzy inference system. To evaluate the performance of intuitionistic fuzzy time series functions, twenty-three real-world time series data sets are analyzed. The results obtained from the intuitionistic fuzzy time series functions approach are compared with some other methods according to a root mean square error and mean absolute percentage error criteria. The proposed method has superior forecasting performance among all methods

Extension of Axiomatic Design Method for Fuzzy Linguistic Multiple Criteria Group Decision Making with Incomplete Weight Information

Axiomatic design (AD) provides a framework to describe design objects and a set of axioms to evaluate relations between intended functions and means by which they are achieved. It has been extended to evaluate alternatives in engineering under fuzzy environment. With respect to multiple criteria group decision making (MCDM) with incomplete weight information under fuzzy linguistic environment, a new method is proposed. In the method, the fuzzy axiomatic design based on triangle representation model is used to aggregate the linguistic evaluating information. In order to get the weight vector of the criteria, we establish a nonlinear optimization model based on the basic ideal of fuzzy axiomatic design (FAD), by which the criteria weights can be determined. It is based on the concept that the optimal alternative should have the least weighted information content. Then, the weighted information content is derived by summing weighted information content for each criterion. The alternative that has the least total weighted information content is the best. Finally, a numerical example is used to illustrate the availability of the proposed method

Extension of Axiomatic Design Principles for Multicriteria Decision Making Problems in Intuitionistic Fuzzy Environment

Axiomatic Design (AD) principles have been used to resolve the multicriteria decision making (MCDM) problems in engineering. With respect to MCDM problems in intuitionistic fuzzy environment, in which the criteria values take the form of intuitionistic fuzzy numbers, a new MCDM method is developed. Firstly, the approach proposed by Chen is extended to aggregate the decision makers’ opinions in intuitionistic fuzzy environment. Secondly, membership common area and nonmembership common area are derived from the membership probability density function and the nonmembership probability density function, respectively. Then the membership information content and nonmembership information content are obtained based on the basic ideal of axiomatic design principles. Afterwards, the score function S and accuracy function H in intuitionistic fuzzy sets are extended with the information content to compare the alternatives. The alternatives that have the lowest values of functions of S and H are the best. Finally, a numerical example is used to illustrate the availability of the proposed method

Capturing Software Architecture Knowledge for Pattern-Driven Design

Context: Software architecture is a knowledge-intensive field. One mechanism for storing architecture knowledge is the recognition and description of architectural patterns. Selecting architectural patterns is a challenging task for software architects, as knowledge about these patterns is scattered among a wide range of literature. Method: We report on a systematic literature review, with the aim of building a decision model for the architectural pattern selection problem. Moreover, twelve experienced practitioners at software-producing organizations evaluated the usability and usefulness of the extracted knowledge.\newline Results: An overview is provided of 29 patterns and their effects on 40 quality attributes. Furthermore, we report in which systems the 29 patterns are applied and in which combinations. The practitioners confirmed that architectural knowledge supports software architects with their decision-making process to select a set of patterns for a new problem. We investigate the potential trends among architects to select patterns. Conclusion: With the knowledge available, architects can more rapidly select and eliminate combinations of patterns to design solutions. Having this knowledge readily available supports software architects in making more efficient and effective design decisions that meet their quality concerns

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

Design and Evaluation of Ballast Water Management Systems using Modified and Hybridised Axiomatic Design Principles

There are two major motivations to this research. The first is based on the concerns raised at the International Maritime Organisation (IMO) MEPC 67 and 68 meetings regarding the capacity of some type-approved Ballast Water Management (BWM) Systems to meet the performance standard (D-2) of the BWM Convention at-all-times and in all conditions. The second is based on the reluctance expressed by some ship- owners to install the system onboard their ships as a Lloyd\u27s list survey suggested. In this work, an attempt was made to address these issues and concerns using a set of criteria stipulated in Regulation D-5.2 of the BWM Convention which provides the framework for reviewing and evaluating the practical concepts of managing ballast water, developing a conceptual model for managing ballast water and minimizing the contributions of human-error to BWM System performance by analyzing the associated operational human factors. Firstly, the design of a conceptual model of managing ballast water and the evaluation of some established practical concepts of BWM were achieved by using a suitable technique (Axiomatic Design or AD) which was selected via a robust procedure. The two axioms of Axiomatic Design (information and independence) were used to evaluate four different concepts of managing ballast water as well as develop a BWM Convention-compliant conceptual design matrix model respectively. Based on data collected from ballast water management experts, Post-loading Onshore Ballast Water Management System was shown to be the most appropriate ballast water management concept with respect to the Regulation D-5.2 set of criteria. This presents a paradigm shift in expert preference from traditional shipboard systems to onshore systems with respect to the IMO-criteria. The pathway for improved performance of the Convention-compliant design matrix was subsequently determined and prioritised using Sufield model of Altshuler\u27s theory of inventive problem solving (TRIZ). Lastly, a 5-step algorithm was developed to minimise operator errors in the BWM System’s operation. Fatigue and training were found to have the greatest impact on operator performance

Advanced Safety Methodology for Risk Management of Petroleum Refinery Operations

Petroleum refineries are important facilities for refining petroleum products that provide the primary source of energy for domestic and industrial consumption globally. Petroleum refinery operations provide significant contribution to global economic growth. Petroleum refineries are complex, multifaceted systems that perform multiple phase operations characterized by a high level of risk. Evidence based major accidents that have occurred within the last three decades in the petroleum refineries, around the world, indicates losses estimated in billions of US dollars. Many of these accidents are catastrophes, which have led to the disruption of petroleum refinery operations. These accidents have resulted in production loss, asset damage, environmental damage, fatalities and injuries. However, the foremost issue analysed in literatures in relation to major accidents in petroleum refineries, is the lack of robust risk assessment and resourceful risk management approaches to identify and assess major accident risks, in order to prevent or mitigate them from escalating to an accident. Thus, it is exceptionally critical to readdress the issue of petroleum refinery risk management with the development of a more dependable, adaptable and holistic risk modelling framework for major accident risks investigation. In this thesis, a proactive framework for advanced risk management to analyse and mitigate the disruption risks of petroleum refinery operations is presented. In this research, various risk elements and their attributes that can interact to cause the disruption of PRPU operations were identified and analysed, in order to determine their criticality levels. This thesis shows that the convergent effect of the interactions between the risk elements and their attributes can lead to the disruption of petroleum refinery operations. In the scheme of the study, Fuzzy Linguistic Preference Relation (FLPR), Fuzzy Evidential Reasoning (FER) and Fuzzy Bayesian Network (FBN) methodologies were proposed and implemented to evaluate the criticality of the risk elements and their attributes and to analyse the risk level of PRPU operations. Also, AHP-fuzzy VIKOR methodology was utilised for decision modelling to determine the optimal strategy for the risk management of the most significant risk elements’ attributes that can interact to cause the disruption of PRPU operations. The methodologies proposed and implemented in this research can be utilised in the petroleum refining industry, to analyse complex risk scenarios where there is incomplete information concerning risk events or where the probability of risk events is uncertain. The result of the analysis conducted in this research to determine the risk level of petroleum refinery operations can be utilised by risk assessors and decision makers as a threshold value for decision making in order to mitigate the disruption risk of PRPU operations. The decision strategies formulated in this thesis based on robust literature review and expert contributions, contributes to knowledge in terms of the risk management of petroleum refinery operations. The result of the evaluation and ranking of the risk elements and their attributes can provide salient risk information to duty holders and decision makers to improve their perceptions, in order to prioritise resources for risk management of the most critical attributes of the risk elements. Overall, the methodologies applied in this thesis, can be tailored to be utilised as a quantitative risk assessment tool, by risk managers and decision analysts in the petroleum refining industry for enhancement risk assessment processes where available information can sometimes be vague or incomplete for risk analysis