Supplier evaluation and selection in fuzzy environments: a review of MADM approaches

In past years, the multi-attribute decision-making (MADM) approaches have been extensively applied by researchers to the supplier evaluation and selection problem. Many of these studies were performed in an uncertain environment described by fuzzy sets. This study provides a review of applications of MADM approaches for evaluation and selection of suppliers in a fuzzy environment. To this aim, a total of 339 publications were examined, including papers in peer-reviewed journals and reputable conferences and also some book chapters over the period of 2001 to 2016. These publications were extracted from many online databases and classified in some categories and subcategories according to the MADM approaches, and then they were analysed based on the frequency of approaches, number of citations, year of publication, country of origin and publishing journals. The results of this study show that the AHP and TOPSIS methods are the most popular approaches. Moreover, China and Taiwan are the top countries in terms of number of publications and number of citations, respectively. The top three journals with highest number of publications were: Expert Systems with Applications, International Journal of Production Research and The International Journal of Advanced Manufacturing Technology

Evaluation of learning management systems using interval valued intuitionistic fuzzy-z numbers

The use of online education tools has increased rapidly with the transition to distance education caused by the pandemic. The obligation to carry out all activities of face-to-face education online made it very important for the tools used in distance education to meet the increasing needs. In line with these needs, radical changes have occurred in the learning management systems used in distance education. Therefore, in this study, it is aimed to determine the features that the systems used in distance education should have and to compare the existing systems according to these features. For this purpose, a novel fuzzy extension, interval valued intuitionistic fuzzy Z-numbers, is defined for modeling uncertainty, and AHP and WASPAS methods using proposed fuzzy numbers are developed to determine the importance of decision criteria and compare alternatives.WOS:0010834495000112-s2.0-85173691458Emerging Sources Citation IndexArticleUluslararası işbirliği ile yapılmayan - HAYIRKasım2023YÖK - 2022-23Eki

An integrated approach for solving a MCDM problem, Combination of Entropy Fuzzy and F-PROMETHEE techniques

Purpose: The intention of this paper is the presentation of a new integrated approach for solving a multi attribute decision making problem by the use of Entropy Fuzzy and F- PROMETHEE (fuzzy preference ranking method for enrichment evaluation) techniques. Design/methodology/approach: In these sorts of multi attribute decision making problem, a number of criteria and alternatives are put forward as input data. Ranking of these alternatives according to mentioned criteria is regarded as the outcome of solving these kinds of problems. Initially, weights of criteria are determined by implementation of Entropy Fuzzy method. According to determined weights, F-PROMETHEE method is exerted to rank these alternatives in terms of desirability of DM (decision maker). Findings: Being in an uncertain environment and vagueness of DM’s judgments, lead us to implement an algorithm which can deal with these constraints properly. This technique namely called Entropy Fuzzy as a weighting method and F-PROMETHEE is performed to fulfill this approach more precisely according to tangible and intangible aspects. The main finding of applied approach is the final ranking of alternatives helping DM to have a more reliable decision. Originality/Value: The main contribution of this approach is the giving real significance to DM’s attitudes about mentioned criteria in determined alternatives which is not elucidate in former approaches like Analytical Hierarchy Process (AHP). Furthermore, previous methods like Shanon Entropy do not pay attention sufficiently to satisfaction degree of each criterion in proposed alternatives, regarding to DM’s statements. Comprehensive explanations about these procedures have been made in miscellaneous sections of this article.Peer Reviewe

An Intuitionistic Fuzzy Group Decision-Making to Measure the Performance of Green Supply Chain Management with TOPSIS Method

Green supply chain management (GSCM) integrates environmental regulations into supply chain management to diminish the negative effects of supply chain processes on the environment. The environmental problems appeared by an enterprise arise from designing the product and last until the recycling process. GSCM activities include five drivers such as green design, green purchasing, green transformation, green logistics and reverse logistics. In this chapter, the main aim is to explain these drivers and to show how to measure the GSCM success of companies, which operate as tire manufacturers by using an evaluation of a group of experts in their field. The proposed method, intuitionistic fuzzy technique for order preference by similarity to an ideal solution as an effective group decision-making method, helped to identify the alternative company 1 with the best GSCM performance among six different alternative tire companies under the consideration of five important GSCM drivers. The ranking result was as follows: A1 > A3 > A4 > A2 > A6 > A5