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Статті в журналах з теми "Fuzzy selection"

Автор: Grafiati

Опубліковано: 3 червня 2025

Оновлено: 31 липня 2025

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1

Ramze Rezaee, M., B. Goedhart, B. P. F. Lelieveldt, and J. H. C. Reiber. "Fuzzy feature selection." Pattern Recognition 32, no. 12 (1999): 2011–19. http://dx.doi.org/10.1016/s0031-3203(99)00005-9.

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2

K, Afsath, and Linjesh Sebastian. "Fuzzy MATLAB Approach to Construction Contractor Selection." International Journal of Scientific Engineering and Research 4, no. 8 (2016): 45–49. https://doi.org/10.70729/ijser15919.

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3

Roh, Seok-Beom, Yong Soo Kim, and Tae-Chon Ahn. "Feature Selection of Fuzzy Pattern Classifier by using Fuzzy Mapping." Journal of Korean Institute of Intelligent Systems 24, no. 6 (2014): 646–50. http://dx.doi.org/10.5391/jkiis.2014.24.6.646.

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4

Tafazzoli, Mohammadsoroush, Ayoub Hazrati, Kishor Shrestha, and Krishna Kisi. "Enhancing Contractor Selection through Fuzzy TOPSIS and Fuzzy SAW Techniques." Buildings 14, no. 6 (2024): 1861. http://dx.doi.org/10.3390/buildings14061861.

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Анотація:

Contractors play an integral role in construction projects, and their qualifications directly impact various aspects of a project’s success. The unbiased selection of contractors is a challenge in the construction industry worldwide, particularly in public projects where impartiality in the final selection is essential. Numerous factors must be considered when evaluating contractors, making the selection process challenging for the human brain. This paper introduces and compares two methods for assessing contractor prequalification by applying the fuzzy theory. The idea is to facilitate using

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5

Beseiso, Majdi, and Gulshan Kumar. "A fuzzy computational approach for selecting interdependent projects using prioritized criteria." Journal of Intelligent & Fuzzy Systems 40, no. 6 (2021): 11341–54. http://dx.doi.org/10.3233/jifs-202506.

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This paper presents a fuzzy computational approach for selecting project portfolio by combining fuzzy logic, Quality Function Deployment (QFD) and Genetic algorithm (GA) approaches with the consideration of prioritized selection criteria as per objectives of the organization to make decisions effectively with incomplete and ambiguous information to help in portfolio selection. This approach addresses the issues of the uncertainty of experts in selecting projects, prioritizing criteria before initiating project selection process and evaluating the number of interdependent projects for their max

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6

Ghaffari, S., and MR Homaeinezhad. "Autonomous path following by fuzzy adaptive curvature-based point selection algorithm for four-wheel-steering car-like mobile robot." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 232, no. 15 (2017): 2655–65. http://dx.doi.org/10.1177/0954406217723363.

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Autonomous path following in mobile robots with nonholonomic constraints can be divided into two problems: first, selecting the tracking point, and then designing an appropriate controller to follow the selected point. When selecting tracking point, considering the kinematics of the robot as well as characteristics of the desired path is of considerable importance. For these purposes, a curvature-based point selection algorithm is first proposed for the car-like mobile robot with independent steering mechanisms. Each instant, the proposed algorithm finds a point which enables the robot to be t

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7

BASHIRI, MAHDI, HOSSEIN BADRI, and JAFAR TALEBI. "A NEW FUZZY APPROACH FOR PROJECT SELECTION WITH OUTSOURCING VIEWPOINT." International Journal of Innovation and Technology Management 08, no. 02 (2011): 227–51. http://dx.doi.org/10.1142/s0219877011002349.

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Анотація:

Nowadays most of the organizations tend to outsource their projects. In these cases, two major problems arise: project selection and contractor selection. There are many papers which have argued separately about project and contractor selections. In this paper, we propose a decision support system for selecting projects and related contractors. The proposed approach contains three phases including contractors' prequalification (Phase 1), computing success coefficient of each contractor in projects using fuzzy TOPSIS method (Phase 2), and selecting projects and assigning each project to the mos

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8

Vasanti, G., and B. Venkata Rao. "Fuzzy Modelling for Selection of Overall Best Performer." DJ Journal of Engineering and Applied Mathematics 2, no. 1 (2016): 1–6. http://dx.doi.org/10.18831/djmaths.org/2016011001.

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9

Tinda Mangongo, Yves, Christian Tassak Deffo, Louis Aime Fono, Joseph Desire Kyemba Bukweli, and Justin Dupar Busili Kampempe. "Portfolio Selection with fuzzy return without target values." International Journal of Scientific Engineering and Research 6, no. 1 (2018): 18–29. https://doi.org/10.70729/ijser172072.

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10

Petrovic‐Lazarevic, Sonja. "Personnel Selection Fuzzy Model." International Transactions in Operational Research 8, no. 1 (2001): 89–105. http://dx.doi.org/10.1111/1475-3995.00008.

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11

POLAT, Gul, Ekin ERAY, and Befrin Neval BINGOL. "AN INTEGRATED FUZZY MCGDM APPROACH FOR SUPPLIER SELECTION PROBLEM." Journal of Civil Engineering and Management 23, no. 7 (2017): 926–42. http://dx.doi.org/10.3846/13923730.2017.1343201.

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Анотація:

Materials constitute a large proportion of the total project cost and the absence of right materials in the right quantities and quality on site when needed is one of the most commonly experienced causes of delays in construction projects. Although supplier selection is a strategic issue, contractors generally select suppliers based on their past experiences, which may result in selecting wrong suppliers. Supplier selection decision is generally made by multiple decision makers and is affected by several criteria. Therefore, selecting the right supplier among many alternatives considering sev

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12

Bendaña, Ricardo, Alfredo del Caño, and M. Pilar de la Cruz. "Contractor selection: fuzzy-control approach." Canadian Journal of Civil Engineering 35, no. 5 (2008): 473–86. http://dx.doi.org/10.1139/l07-127.

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Анотація:

This paper presents a fuzzy-logic-based system for selecting contractors. This tool, which was based on the fuzzy control technique, was created for the private sector client in traditional design–bid–build projects with one-step selection processes, but its philosophy can also serve other types of clients, industries, contracts, and selection processes. The system develops an assessment of different qualitative and quantitative issues that influence a contractor’s suitability for constructing a specific design in a specific environment (client’s needs and objectives, objectives prioritization

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13

Tiryaki, Fatma, and Beyza Ahlatcioglu. "Fuzzy portfolio selection using fuzzy analytic hierarchy process." Information Sciences 179, no. 1-2 (2009): 53–69. http://dx.doi.org/10.1016/j.ins.2008.07.023.

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14

Kim, Won-Kyu, Kyoo-Hong Park, and Kyoung-Hee Lee. "Fuzzy selection and existence of fuzzy fixed point." Korean Journal of Computational & Applied Mathematics 2, no. 1 (1995): 17–23. http://dx.doi.org/10.1007/bf03008954.

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15

Matawale, Chhabi Ram, Saurav Datta, and S. S. Mahapatra. "Supplier selection in agile supply chain." Benchmarking: An International Journal 23, no. 7 (2016): 2027–60. http://dx.doi.org/10.1108/bij-07-2015-0067.

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Анотація:

Purpose The recent global market trend is seemed enforcing existing manufacturing organizations (as well as service sectors) to improve existing supply chain systems or to take up/adapt advanced manufacturing strategies for being competitive. The concept of the agile supply chain (ASC) has become increasingly important as a means of achieving a competitive edge in highly turbulent business environments. An ASC is a dynamic alliance of member enterprises, the formation of which is likely to introduce velocity, responsiveness, and flexibility into the manufacturing system. In ASC management, sup

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16

Ahmad Taharim, Mohd Ariff, and Liew Kee Kor. "Application of fuzzy technique for order preference by similarity to the ideal solution in the selection of candidates." Social and Management Research Journal 9, no. 1 (2012): 35. http://dx.doi.org/10.24191/smrj.v9i1.5211.

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Анотація:

Selecting the right candidate for the right cause is similar to identifying the most compromising solution of multi-criteria decision making (MCDM) problem. In real life the selection criteriamay involve vague and incomplete data which cannot be expressed in precise mathematical form or numerical values. Apparently fuzzy-based technique can be applied to describe and represent these data in fuzzy numbers. This paper presents a MCDM fuzzy TOPSIS based model designed to solve the selection problemfor allocation of government staff quarters. Result shows that the proposed model is suitable and ap

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17

Huynh, Nguyen Tan. "Supplier selection by using the fuzzy analytic hierarchy process." Journal of Development and Integration, no. 77 (August 26, 2024): 2–9. http://dx.doi.org/10.61602/jdi.2024.77.01.

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It has been argued that supplier selection is of paramount importance for production companies. In particular, selecting appropriate suppliers may improve production outputs’ quality for firms. Until date, some methods have been developed to select suppliers; yet, some weaknesses still exist. To fill the literature gap, this paper aims to set up a model for judging and selecting potential suppliers from manufactures’ perspectives by the fuzzy Analytic Hierarchy Process (fuzzy AHP). It is posulated that fuzzy AHP is not only applicable for supplier selection, but also helpful in assessing staff

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18

Sarfaraz, A. "A Fuzzy Conceptual Design Selection Model Considering Conflict Resolution." International Journal of Engineering and Technology 4, no. 1 (2012): 38–45. http://dx.doi.org/10.7763/ijet.2012.v4.315.

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19

Jiang, Yanling, Shangzhu Jin, and Jun Peng. "Hierarchical Fuzzy Rule Interpolation and its Application for Hotels Location Selection." International Journal of Cognitive Informatics and Natural Intelligence 10, no. 1 (2016): 55–79. http://dx.doi.org/10.4018/ijcini.2016010104.

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Анотація:

Fuzzy rule interpolation offers a useful means for enhancing the robustness of fuzzy models by making inference possible in systems of only a sparse rule base. However in practical applications, as the application domain of fuzzy systems expand to more complex ones, the curse of dimensionality problem of the conventional fuzzy systems became apparent, which makes the already challenging tasks such as inference and interpolation even more difficult. An initial idea of hierarchical fuzzy interpolation is presented in this paper. The proposed approach combines hierarchical fuzzy systems and fuzzy

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20

Nurcahyo, Gunadi Widi, and Alexyusandria Alexyusandria. "MODIFIED SWEEP ALGORITHM FOR ROUTE SELECTION IN PUBLIC BUS ROUTING PROBLEM USING FUZZY DATA." Elektron : Jurnal Ilmiah 4, no. 2 (2012): 49–56. http://dx.doi.org/10.30630/eji.4.2.31.

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This paper investigates public bus route selection where demand is uncertain and evaluates the role of fuzzy logic in the MSA. The uncertain demand data are presented in linguistic form and transformed into fuzzy numbers. The crisp values obtained by the fuzzy logic are used to replace the exact demand in selecting best routes. The patterns of fuzzy data are presented to show capability of fuzzy data in representing exact data.

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21

Tronnebati, Imane, Fouad Jawab, Youness Frichi, and Jabir Arif. "Green Supplier Selection Using Fuzzy AHP, Fuzzy TOSIS, and Fuzzy WASPAS: A Case Study of the Moroccan Automotive Industry." Sustainability 16, no. 11 (2024): 4580. http://dx.doi.org/10.3390/su16114580.

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The green supplier selection presents numerous challenges, from initial assessment to final selection, which specialists in this field of supplier management often encounter. Among the techniques that aim to meet these challenges that are continually progressing is the creation and development of high-quality decision-making tools. In this study, the assessment of suppliers hinges on both traditional and environmental factors. A framework of multi-criteria decision-making (MCDM) is announced in order to appraise green supplier selection. This framework integrates Fuzzy Analytical Hierarchy Pro

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22

FASANGHARI, MEHDI, MOHSEN SADEGH AMALNICK, S. KAMAL CHAHARSOOGHI, and FRANZ I. S. KO. "THE FUZZY EVALUATION OF THE ICT PROJECTS IN STRATEGIC ENVIRONMENT (CASE STUDY: IRAN TELECOMMUNICATION RESEARCH CENTER)." International Journal of Information Technology & Decision Making 10, no. 05 (2011): 873–90. http://dx.doi.org/10.1142/s0219622011004610.

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Many criteria should be considered for project selection in Information and Communication Technology (ICT) sectors; while, the resources are limited. Besides, the uncertainty of the selection and evaluation process increases the difficulty of ICT project selection. Therefore, a fuzzy system in combination with fuzzy integer linear programming, fuzzy entropy, and fuzzy numbers have been developed; it smoothes the process of ICT project selection. This fuzzy system is flexible in the project selection for Iran ICT sectors, especially in (Research and Development) R&D sectors. It enhances the

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23

Afshari, A. R., and R. M. Yusuff. "Fuzzy Integral Project Manager Selection." Australian Journal of Multi-Disciplinary Engineering 9, no. 2 (2013): 149–54. http://dx.doi.org/10.7158/14488388.2013.11464855.

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24

Ali, M. Ameer, Nikhil C. Shil, M. S. Q. Zulkar Nine, M. A. K. Khan, and Mahedi H. Hoque. "Vendor selection using fuzzy integration." International Journal of Management Science and Engineering Management 5, no. 5 (2010): 376–82. http://dx.doi.org/10.1080/17509653.2010.10671128.

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25

Šindelář, Radek. "Input Selection for Fuzzy Modelling." IFAC Proceedings Volumes 37, no. 16 (2004): 13–18. http://dx.doi.org/10.1016/s1474-6670(17)30843-1.

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26

Vieira, Susana M., João M. C. Sousa, and Uzay Kaymak. "Fuzzy criteria for feature selection." Fuzzy Sets and Systems 189, no. 1 (2012): 1–18. http://dx.doi.org/10.1016/j.fss.2011.09.009.

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27

Qian, Yuhua, Qi Wang, Honghong Cheng, Jiye Liang, and Chuangyin Dang. "Fuzzy-rough feature selection accelerator." Fuzzy Sets and Systems 258 (January 2015): 61–78. http://dx.doi.org/10.1016/j.fss.2014.04.029.

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28

Huang, Xiaoxia. "Fuzzy chance-constrained portfolio selection." Applied Mathematics and Computation 177, no. 2 (2006): 500–507. http://dx.doi.org/10.1016/j.amc.2005.11.027.

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29

Huang, Xiaoxia. "Portfolio selection with fuzzy returns." Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology 18, no. 4 (2007): 383–90. https://doi.org/10.3233/ifs-2007-00356.

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30

Aydoğmuş, Hacer Yumurtacı, Eren Kamber, and Cengiz Kahraman. "ERP selection using picture fuzzy CODAS method." Journal of Intelligent & Fuzzy Systems 40, no. 6 (2021): 11363–73. http://dx.doi.org/10.3233/jifs-202564.

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Анотація:

The purpose of this study is to develop an extension of CODAS method using picture fuzzy sets. In this respect, a new methodology is introduced to figure out how picture fuzzy numbers can be applied to CODAS method. COmbinative Distance-based Assessment (CODAS) is a new MCDM method proposed by Ghorabaee et al. Picture fuzzy sets (PFSs) are a new extension of ordinary fuzzy sets for representing human’s judgments having possibility more than two answers such as yes, no, refusal and neutral. Compared with other studies, the proposed method integrates multi-criteria decision analysis with picture

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31

Mohd., Nazim, Hassan Tanveer, Sadiq Mohd., and Wali Mohammad Chaudhary. "An Integrated Method for the Selection of Software Requirements Using Fuzzy TOPSIS and Genetic Algorithm." International Journal of Innovative Science and Research Technology 7, no. 9 (2022): 1792–800. https://doi.org/10.5281/zenodo.7237972.

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Software requirements selection is one of the key activities of the software development process. In this activity the requirements are selected based on their ranking order. Various methods have been developed for selecting the requirements using fuzzy logic, rough set theory, and Metaheuristic algorithms, etc. One of the limitations of the fuzzy based methods is that the membership functions of fuzzy numbers are manually decided by the decision makers. In these methods less attention is given to the automated generation of fuzzy membership function. To address this issue, this paper presents

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32

Bozanic, Darko, Duško Tešić, Dragan Marinkovic, and Aleksandar Milić. "Modeling of neuro-fuzzy system as a support in decision-making processes." Reports in Mechanical Engineering 2, no. 1 (2021): 222–34. http://dx.doi.org/10.31181/rme2001021222b.

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In the paper is presented Neuro-Fuzzy System as a decision-making support in the selection of construction machines (the example of selecting a loader is provided). Construction characteristics of a loader make the basis for selection, but also other elements of importance. The data for Neuro-Fuzzy System modeling are prepared using the Multi-Criteria Decision Making (MCDM) methods: Logarithm Methodology of Additive Weights (LMAW), VIKOR, TOPSIS, MOORA and SAW. The paper also presents the method of aggregation of weights of rules premises (AWRP), which defines the key rules of Neuro-Fuzzy Syst

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33

Utomo, Dutho Suh, Dedy Cahyadi, Indah Fitri Astuti, and Gubtha Mahendra Putra. "Selection of promotional media on tourist boats with fuzzy AHP and fuzzy TOPSIS." International Journal of ADVANCED AND APPLIED SCIENCES 10, no. 5 (2023): 140–48. http://dx.doi.org/10.21833/ijaas.2023.05.017.

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The tourism sector necessitates effective promotion to introduce tourist attractions, including tourist boats operating on the Mahakam River. Given the prevalence of the digital era, it is imperative to employ appropriate promotional channels that precisely target the intended audience. The selection of promotional media entails various criteria and alternatives, thereby making it highly suitable to employ a multi-criteria decision-making approach. Due to the inherent uncertainty in assessments, a fuzzy scale becomes indispensable. This research utilizes a combination of Fuzzy Analytic Hierarc

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34

Alguliyev, Rasim M., Ramiz M. Aliguliyev, and Rasmiyya S. Mahmudova. "Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method." Scientific World Journal 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/612767.

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Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM) model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five i

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35

Utomo, Denny, Pratikto Pratikto, Purnomo Budi Santoso, and Sugiono Sugiono. "Implementation of a fuzzy decision support system for selection of hand tractor assembly suppliers." EUREKA: Physics and Engineering, no. 1 (January 10, 2022): 44–52. http://dx.doi.org/10.21303/2461-4262.2022.001864.

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Supplier selection is a complex problem in the current Industry 4.0 era. The large number of suppliers with different performance qualities makes it difficult for the company's internal parties to choose the appropriate supplier. The suitability of quality suppliers needed to supply raw materials needed by the industry is an important matter to be resolved. In the hand tractor assembly industry, this small and medium industry is also very dependent on the availability of supply materials, and of course it also depends on the selection of the supplier itself. In this study, the object of resear

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36

Utomo, Denny, Pratikto Pratikto, Purnomo Budi Santoso, and Sugiono Sugiono. "Implementation of a fuzzy decision support system for selection of hand tractor assembly suppliers." EUREKA: Physics and Engineering, no. 1 (January 10, 2022): 44–52. https://doi.org/10.21303/2461-4262.2022.001864.

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Анотація:

Supplier selection is a complex problem in the current Industry 4.0 era. The large number of suppliers with different performance qualities makes it difficult for the company's internal parties to choose the appropriate supplier. The suitability of quality suppliers needed to supply raw materials needed by the industry is an important matter to be resolved. In the hand tractor assembly industry, this small and medium industry is also very dependent on the availability of supply materials, and of course it also depends on the selection of the supplier itself. In this study, the object of resear

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37

Jiang, Hua, and Zhi Gang Lu. "A Fuzzy Programming Model of Supplier Selection." Advanced Materials Research 468-471 (February 2012): 668–73. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.668.

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Анотація:

An integrated supplier selection problem under fuzzy environment is studied in this paper. Firstly, the linear weight method is used to calculate the scores of suppliers according to their different attributes, such as: quality, service, warranty, delivery, reputation and position, which are assumed as fuzzy variables. Secondly, a fuzzy expected value programming model and a fuzzy chance-constrained programming model are proposed to select the best combination of the suppliers and determine the order quantities. A hybrid intelligent algorithm, based on fuzzy simulation, genetic algorithm and n

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38

Li, Zhi-Min, and Yi-Ding Zhao. "Model for Software Patterns Selection with Fuzzy Linguistic Information." Journal of Computational and Theoretical Nanoscience 13, no. 10 (2016): 7533–37. http://dx.doi.org/10.1166/jctn.2016.5749.

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Анотація:

With respect to multiple attribute group decision making problem with triangular fuzzy linguistic information, in which the attribute weights and expert weights take the form of real numbers, and the preference values take the form of triangular fuzzy linguistic variables, some operators for aggregating triangular fuzzy linguistic variables, such as the fuzzy linguistic harmonic mean (FLHM) operator, fuzzy linguistic weighted harmonic mean (FLWHM) operator, fuzzy linguistic ordered weighted harmonic mean (FLOWHM) operator, and fuzzy linguistic hybrid harmonic mean (FLHHM) operator are proposed

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39

Aliyeva, Kamala Rafig. "Application Fuzzy AHP-TOPSÄ°S Hybrid Method in Facility Location Selection for Software Systems." Ultimatics : Jurnal Teknik Informatika 16, no. 2 (2025): 76–83. https://doi.org/10.31937/ti.v16i2.3545.

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Анотація:

Facility location is an integral part of the strategic planning process of almost every organization. Selecting the right location for software systems facilities involves considering various factors to ensure optimal performance, reliability, and cost-effectiveness. For business success, and competitive advantage there are some critical factors that very highly affect facility location. They are proximity to customers, infrastructure, labor quality, total cost, suppliers, etc. The criteria for selecting a facility location may be vaguely defined or open to interpretation. External factors suc

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40

Aliyeva, Kamala Rafig. "Application of Fuzzy AHP-TOPSÄ°S Hybrid Method in Facility Location Selection for Software Systems." Ultimatics : Jurnal Teknik Informatika 17, no. 1 (2025): 34–41. https://doi.org/10.31937/ti.v17i1.3602.

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Анотація:

- Facility location is an integral part of the strategic planning process of almost every organization. Selecting the right location for software systems facilities involves considering various factors to ensure optimal performance, reliability, and cost-effectiveness. For business success, and competitive advantage there are some critical factors that very highly affect facility location. They are proximity to customers, infrastructure, labor quality, total cost, suppliers, etc. The criteria for selecting a facility location may be vaguely defined or open to interpretation. External factors s

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41

Sampathkumar, Swethaa, Felix Augustin, Mohammed KA Kaabar, and Xiao-Guang Yue. "An integrated intuitionistic dense fuzzy Entropy-COPRAS-WASPAS approach for manufacturing robot selection." Advances in Mechanical Engineering 15, no. 3 (2023): 168781322311602. http://dx.doi.org/10.1177/16878132231160265.

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Анотація:

Manufacturing robots are used for industrial purposes. Robots used for manufacturing purpose have the power to create products from raw materials and are capable of operating endlessly even in lights-out situations for continuous production. Manufacturing robots can be used in applications like arc welding, spot welding, materials handling, machine tending, painting, machine cutting and so on. Selecting a robot for a given application is complex. However, robot selection is used in selecting a suitable robot for the preferred output with specific application ability. In recent years, many auth

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LUCHIAN, Andrei-Mihai. "FUZZY MULTI CRITERIAL SELECTION FOR PROMETHEUS DECISIONS IN MILITARY APPLICATIONS." SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 20 (June 18, 2018): 203–10. http://dx.doi.org/10.19062/2247-3173.2018.20.26.

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Rajput, Virendra, Rohit Soni, Animesh Singhai, Dinesh Singh Yadav, Surendra Kushwah, and Dharmendra Tikle. "A Literature Review on Fuzzy-TOPSIS Approach in Material Selection." International Journal of Research Publication and Reviews 5, no. 1 (2024): 4953–56. http://dx.doi.org/10.55248/gengpi.5.0124.0349.

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Yan, Zhijia, Wenting Yang, Xiaoling Huang, Xiangrong Shi, and Wenyu Zhang. "A Reputation-Enhanced Hybrid Approach for Supplier Selection with Intuitionistic Fuzzy Evaluation Information." Mathematics 7, no. 3 (2019): 298. http://dx.doi.org/10.3390/math7030298.

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Анотація:

Selecting optimal suppliers in fuzzy environments has become a major challenge for enterprises. Reputation plays an important role in the process of supplier selection because of its fuzziness, dynamicity, and transitivity. In this study, we first present a novel intuitionistic fuzzy sets (IFS)-hyperlink-induced topic search (HITS) method that combines the intuitionistic fuzzy set with the hyperlink-induced topic search (HITS) algorithm to extend the ability of processing fuzzy information in order to obtain post-propagated reputation values of suppliers. Then, we employ the dynamic intuitioni

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KESHAVARZ GHORABAEE, Mehdi, Maghsoud AMIRI, Edmundas Kazimieras ZAVADSKAS, Reyhaneh HOOSHMAND, and Jurgita ANTUCHEVIČIENĖ. "FUZZY EXTENSION OF THE CODAS METHOD FOR MULTI-CRITERIA MARKET SEGMENT EVALUATION." Journal of Business Economics and Management 18, no. 1 (2017): 1–19. http://dx.doi.org/10.3846/16111699.2016.1278559.

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Анотація:

One of the important activities of a company that can increase its competitiveness is market segment evaluation and selection (mse/mss). We can usually consider mse/mss as a multi-criteria decision-making (mcdm) problem, and so we need to use an mcdm method to handle it. Uncertainty is one of the important factors that can affect the process of decision-making. Fuzzy mcdm approached have been designed to deal with the uncertainty of decision-making problems. In this study, a fuzzy extension of the codas (combinative distance-based assessment) method is proposed to solve multi-criteria group de

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Santoso, Jaya, Asido Saragih, and Ana Muliyana. "Application of Tahani Fuzzy Logic in Participant Selection for ONMIPA PT: A Case Study at Institut Teknologi Del." EduMatSains : Jurnal Pendidikan, Matematika dan Sains 9, no. 2 (2025): 180–91. https://doi.org/10.33541/edumatsains.v9i2.6273.

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Анотація:

This study investigates the preparation of students for the National Olympiad of Mathematics and Natural Sciences for Higher Education (ONMIPA PT), focusing on the selection process at Institut Teknologi Del (IT Del). The research applies the Tahani fuzzy logic method to select students who demonstrate potential across various mathematical disciplines such as Linear Algebra, Abstract Algebra, Real Analysis, Complex Analysis, and Combinatorics. By using fuzzy logic, students' performances are categorized into three levels: less, adequate, and good. The goal is to ensure a well-rounded selection

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Çıkmak, Sinan. "Sustainable 3PL Service Provider Selection in the Pharmaceutical Industry Using Fuzzy-Based SWARA and MAIRCA Methods." Abant Sosyal Bilimler Dergisi 25, no. 1 (2025): 306–33. https://doi.org/10.11616/asbi.1585792.

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Анотація:

This study aims to develop a framework for the selection of sustainable third-party logistics service providers (3PLSPs) for the pharmaceutical industry by developing an integrated decision-making framework based on fuzzy SWARA and fuzzy MAIRCA methods. To achieve this goal, 21 selection criteria were determined within the scope of economic, infrastructure, environmental, and social basic dimensions through literature review and expert opinions. Then, the weights of these criteria were calculated using the fuzzy SWARA method. Finally, alternative sustainable 3PLSPs were ranked using the fuzzy

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K. Yogesh Naidu. "Intuitionistic Fuzzy Supplier Selection using Signed Distance and Fuzzy TOPSIS." Journal of Information Systems Engineering and Management 10, no. 23s (2025): 302–9. https://doi.org/10.52783/jisem.v10i23s.3706.

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Анотація:

This research proposes a novel supplier selection approach using Intuitionistic Trapezoidal Fuzzy Numbers (ITFNs), Signed Distance(SD),and Fuzzy TOPSIS. The Signed Distance, a robust metric for measuring the distance between intuitionistic fuzzy sets, is employed to rank ITFNs and compare suppliers based on multiple criteria using Fuzzy TOPSIS. The proposed model effectively handles uncertainty and vagueness in supplier evaluations, providing more flexible and accurate supplier rankings. The supplier selection process is demonstrated with a numerical example.

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Pérez-Domínguez, Luis, Alejandro Alvarado-Iniesta, Iván Rodríguez-Borbón, and Osslan Vergara-Villegas. "Intuitionistic Fuzzy MOORA for Supplier Selection." DYNA 82, no. 191 (2015): 34–41. http://dx.doi.org/10.15446/dyna.v82n191.51143.

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Анотація:

<p class="ADYNAAbstrac"><span lang="EN-US">The supplier selection is a critical activity within the administration of the supply chain. It is considered a complex problem given that it involves different aspects such as the alternatives to evaluate, the multiple criteria involved as well as the group of decision makers with different opinions. In this sense, the literature reports several methods to help in this difficult activity of selecting the best supplier. However, there are still some gaps in these methods; therefore, it is imperative to further develop research. Thus, the p

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ULUTAŞ, Alptekin. "Supplier Selection by Using a Fuzzy Integrated Model for a Textile Company." Engineering Economics 30, no. 5 (2019): 579–90. http://dx.doi.org/10.5755/j01.ee.30.5.20546.

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Анотація:

Supply chain management determining the competitive position of corporations in a rival and fast-changing environment is one of the favourite topics in engineering economics. Since the performance of suppliers affects the performance of the whole supply chain, the selection of a supplier is a significant problem in supply chain management. When solving a supplier selection problem, there are many criteria needed to be considered. Therefore, the supplier selection problem is a multi-criteria decision making (MCDM) problem. In the supplier selection process, most of the time, expert data is invo

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