Theory of fuzzy integrals and its applications

IEEE Transactions on Pattern Analysis and Machine Intelligence

The main advances regarding the use of the Choquet and Sugeno integrals in multi-criteria decision aid over the last decade are reviewed. They concern mainly a bipolar extension of both the Choquet integral and the Sugeno integral, interesting particular submodels, new learning techniques, a better interpretation of the models and a better use of the Choquet integral in multi-criteria decision aid. Parallel to these theoretical works, the Choquet integral has been applied to many new fields, and several softwares and libraries dedicated to this model have been developed.

A decade of application of the Choquet and Sugeno integrals in multi-criteria decision aid

Decision making trial and evaluation laboratory (DEMATEL) is considered as an effective method for the identification of cause-effect chain components of a complex system. It deals with evaluating interdependent relationships among factors and finding the critical ones through a visual structural model. Over the recent decade, a large number of studies have been done on the application of DEMATEL and many different variants have been put forward in the literature. The objective of this study is to review systematically the methodologies and applications of the DEMATEL technique. We reviewed a total of 346 papers published from 2006 to 2016 in the international journals. According to the approaches used, these publications are grouped into five categories: classical DEMATEL, fuzzy DEMATEL, grey DEMATEL, analytical network process- (ANP-) DEMATEL, and other DEMATEL. All papers with respect to each category are summarized and analyzed, pointing out their implementing procedures, real applications, and crucial findings. This systematic and comprehensive review holds valuable insights for researchers and practitioners into using the DEMATEL in terms of indicating current research trends and potential directions for further research.

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DEMATEL Technique: A Systematic Review of the State-of-the-Art Literature on Methodologies and Applications

Multicriteria Pythagorean fuzzy decision analysis

An analysis of DEMATEL approaches for criteria interaction handling within ANP.A classification of the methods related to criteria interaction phenomenon in MADM.Detailed explanations and numerical examples are given.Bibliometric analysis is provided. Majority of the Multiple-Attribute Decision Making (MADM) methods assume that the criteria are independent of each other, which is not a realistic assumption in many real world problems. Several forms of interactions among criteria might occur in real life situations so that more sophisticated/intelligent techniques are required to deal with particular needs of the problem under consideration. Unfortunately, criteria interaction concept is very little issued in the literature. It is still a very important and critical research subject for intelligent decision making within MADM. The present paper aims to put a step forward to fill this gap by depicting the general picture, which provides a classification of methods related to criteria interaction phenomenon, and discuss/review the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) hybridizations first time in the literature. DEMATEL and ANP hybridizations grab remarkable attention of decision analysis community in recent years and seem as one of the most promising approaches to handle criteria interactions in a MADM setting.

An analysis of DEMATEL approaches for criteria interaction handling within ANP

Development of a novel multiple-attribute decision making model via fuzzy cognitive maps and hierarchical fuzzy TOPSIS

Failure mode and effects analysis (FMEA) is a prominent engineering technique for eliminating the potential failures emerged from various systems such as products, processes, designs, or systems. In the traditional FMEA, for each risk factor, severity, occurrence, and detectability ratings are multiplied and risk ranking number (RPN) is calculated. However, traditional FMEA has been subject of severe criticism in the literature and significant efforts have been made to overcome the shortcomings of the RPN. The present paper aims to put a step forward to enhance fuzzy FMEA by proposing a hybrid multi-attribute decision making model by combining fuzzy preference programming, fuzzy cognitive maps, and fuzzy graph-theoretical matrix approach. Fuzzy preference programming method is used to derive ratings of risk factors from incomplete, imprecise, and reciprocal pairwise comparison judgments. The causal dependencies among failure modes are modelled via fuzzy cognitive maps in order to capture the long term influences. Finally, fuzzy graph-theoretical matrix approach is employed to calculate risk priority indices of failure modes by taking into account interactions among risk factors. Although the FMEA method has been implemented in variety of technical problems, its potential in analyzing complex information systems have not been fully explored. Therefore, the proposed model is implemented in evaluating enterprise resource planning implementation risks in a real life case study.

Comprehensive fuzzy FMEA model: a case study of ERP implementation risks

This paper introduces a new binary Grey Wolf Optimization (GWO) algorithm, which is one of the recent swarm intelligence-based metaheuristic algorithms. Its various extensions have been reported in the related literature. Despite numerous successful applications in real-valued optimization problems, the canonical GWO algorithm cannot directly handle binary optimization problems. To this end, transformation functions are commonly employed to map the real-valued solution vector to the binary values; however, this approach brings about the undesired problem of spatial disconnect. In this study, evolutionary and adaptive inheritance mechanisms are employed in the GWO algorithm so as to operate in the binary domain directly. To mimic the leadership hierarchy procedure of the GWO, multi-parent crossover with two different dominance strategies is developed while updating the binary coordinates of the wolf pack. Furthermore, adaptive mutation with exponentially decreasing step-size is adopted to avoid premature convergence and to establish a balance between intensification and diversification. The performance of the proposed algorithm is tested on the well-known binary benchmark suites comprised of the Set-Union Knapsack Problem (SUKP) that extends the 0–1 Knapsack Problem and the Uncapacitated Facility Location Problem (UFLP). Comprehensive experimental study including real-life applications and statistical analyses demonstrate the effectiveness of the proposed algorithm.

Evolutionary and adaptive inheritance enhanced Grey Wolf Optimization algorithm for binary domains

This study presents a new risk assessment model by combining interval type-2 fuzzy best-worst method (IT2F-BWM) and perceptual reasoning for risk evaluation of digital transformation projects. Digital transformations are technology-driven change processes that transform many businesses. Digital transformations are risky and difficult undertakings so that the decision-makers should be supported with appropriate risk assessment tools. The proposed model is a step towards this direction by providing decision-makers with a practical and applicable risk assessment tool that computes with words through a transparent and interpretable reasoning mechanism. In the proposed model, the relative importance of risk factors (RFs) is derived by using IT2F-BWM. Then, IT2F rule-based model is developed by considering risk factors along with the likelihood and severity of risks. The risk magnitudes of digital transformation projects are evaluated via perceptual reasoning. Both the input and output of the reasoning model are IT2F numbers, and the resulting risk magnitudes are decoded into words such as critical, major, and minor so as to ease interpretation. A real-life digital transformation risk assessment case study is conducted in order to demonstrate the applicability of the proposed model.

İlker Gölcük

Papers

An analysis of DEMATEL approaches for criteria interaction handling within ANP

Development of a novel multiple-attribute decision making model via fuzzy cognitive maps and hierarchical fuzzy TOPSIS

Comprehensive fuzzy FMEA model: a case study of ERP implementation risks

Evolutionary and adaptive inheritance enhanced Grey Wolf Optimization algorithm for binary domains

An interval type-2 fuzzy reasoning model for digital transformation project risk assessment