Academic literature on the topic 'Fuzzy multicriteria decision-making'
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Journal articles on the topic "Fuzzy multicriteria decision-making"
Yager, Ronald R. "Multicriteria Decision-Making Using Fuzzy Measures." Cybernetics and Systems 46, no. 3-4 (April 3, 2015): 150–71. http://dx.doi.org/10.1080/01969722.2015.1012884.
Full textGrabisch, Michel. "Fuzzy integral in multicriteria decision making." Fuzzy Sets and Systems 69, no. 3 (February 1995): 279–98. http://dx.doi.org/10.1016/0165-0114(94)00174-6.
Full textZaychenko, Olena Yu, and Yuriy P. Zaychenko. "Multicriteria decision-making problems under fuzzy conditions." System research and information technologies, no. 4 (November 15, 2016): 79–87. http://dx.doi.org/10.20535/srit.2308-8893.2016.4.08.
Full textKahraman, Cengiz, Sezi Cevik Onar, and Basar Oztaysi. "Fuzzy Multicriteria Decision-Making: A Literature Review." International Journal of Computational Intelligence Systems 8, no. 4 (May 2015): 637–66. http://dx.doi.org/10.1080/18756891.2015.1046325.
Full textSatyadas, Antony, and H. C. Chen. "Multicriteria multigoal decision making - the fuzzy paradigm." Computers & Industrial Engineering 23, no. 1-4 (November 1992): 393–96. http://dx.doi.org/10.1016/0360-8352(92)90144-9.
Full textRolka, Leszek, Alicja Mieszkowicz-Rolka, and Grzegorz Drupka. "Multicriteria decision-making in flight route selection." Aircraft Engineering and Aerospace Technology 92, no. 9 (June 3, 2020): 1377–84. http://dx.doi.org/10.1108/aeat-12-2019-0245.
Full textCarnero, María Carmen. "Fuzzy Multicriteria Models for Decision Making in Gamification." Mathematics 8, no. 5 (May 1, 2020): 682. http://dx.doi.org/10.3390/math8050682.
Full textYe, Jufeng. "Aggregation Operators of Trapezoidal Intuitionistic Fuzzy Sets to Multicriteria Decision Making." International Journal of Intelligent Information Technologies 13, no. 4 (October 2017): 1–22. http://dx.doi.org/10.4018/ijiit.2017100101.
Full textCeballos, Blanca, María Teresa Lamata, and David A. Pelta. "Fuzzy Multicriteria Decision-Making Methods: A Comparative Analysis." International Journal of Intelligent Systems 32, no. 7 (December 20, 2016): 722–38. http://dx.doi.org/10.1002/int.21873.
Full textPonsard, Claude. "Spatial fuzzy consumer's decision making: A multicriteria analysis." European Journal of Operational Research 25, no. 2 (May 1986): 235–46. http://dx.doi.org/10.1016/0377-2217(86)90088-3.
Full textDissertations / Theses on the topic "Fuzzy multicriteria decision-making"
Wagholikar, Amol S., and N/A. "Acquisition of Fuzzy Measures in Multicriteria Decision Making Using Similarity-based Reasoning." Griffith University. School of Information and Communication Technology, 2007. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20071214.152324.
Full textCaetani, Alberto Pavlick. "Uso de método multicritério para seleção de estratégia de reconversão industrial em uma refinaria de petróleo." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2014. http://hdl.handle.net/10183/101513.
Full textThis dissertation presents a selection process of industrial reconversion strategy in a small oil refinery in southern Brazil by applying an integrated modeling approach, using a multicriteria and a mathematical programming method. Potentially performing business lines were identified, as well a set of criteria covering the three dimensions of corporate sustainability: economic, social and environmental. Based on the relative importance evaluation of each criteria given by a group of decision-makers, and on performance of the business lines in each of the criteria, fuzzy TOPSIS method was applied for analysis and sorting of business lines. The information resulting from this analysis, along with objective economic data, were used in integer linear programming model to evaluate effective portfolios of business lines, identifying candidate strategies to implement in the refinery. Fuzzy TOPSIS is used to generate overall performance scores of each candidate strategy, aggregating the individual performance of the business lines. The sustainability assessment was analyzed through graphical tools in order to generate information to support the selection of the best strategy for the industrial reconversion. The results demonstrated the efficiency of the proposed approach to facilitate the understanding and exploitation of the problem situation and thus offer adequate support to decision making.
Almulhim, Tarifa Saleh M. "Development of a hybrid fuzzy multi-criteria decision making model for selection of group health insurance plans." Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/development-of-a-hybrid-fuzzy-multicriteria-decision-making-model-for-selection-of-group-health-insurance-plans(9e687f14-38df-45dd-9315-70d18aac6455).html.
Full textJunior, Francisco Rodrigues Lima. "Comparação entre os métodos Fuzzy TOPSIS e Fuzzy AHP no apoio à tomada de decisão para seleção de fornecedores." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/18/18156/tde-12092013-103003/.
Full textSupplier selection has a significant influence on the cost, quality and delivery of products of the buying company. Therefore, supplier selection has become a very critical activity to the performance of the buying company. Several studies presented in the literature propose the use of fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and fuzzy AHP (Analytic Hierarchy Process) to aid the decision process of supplier selection. However, there are no comparative studies of these two methods when applied to the problem of supplier selection. Thus, this paper presents a comparative analysis of the methods fuzzy TOPSIS (Chen, 2000) and fuzzy AHP (Chang, 1996) applied to the problem of supplier selection. A descriptive quantitative approach was adopted as the research method. Algorithms of the methods fuzzy TOPSIS and fuzzy AHP were developed in Matlab© and applied to the selection of suppliers of a company in the automotive production chain. Five suppliers were evaluated regarding quality of conformance, cost, delivery, profile and relationship. The weight of the criteria and the performance of the suppliers were evaluated by specialist opinion from the studied company. The methods Fuzzy TOPSIS e Fuzzy AHP were compared in terms of ability to support the group decision, supplier qualification, final choice of suppliers, buying situations and modeling decisions under uncertainty. The efficiency of the methods with respect to computational complexity and the required user interaction was also compared. The comparative analysis shows that Fuzzy TOPSIS presents better than Fuzzy AHP performance, especially in scenarios in wich many alternatives are evaluated. Thus, Fuzzy TOPSIS is more flexible and appropriate than Fuzzy AHP to deal with supplier selection problem. This paper presents a new study, comparing the methods Fuzzy TOPSIS and Fuzzy AHP. As commented by Ertugrul and Karakasoglu (2008), a study such as this can contribute to the advance of knowledge, helping researchers and practitioners choosing more effective approaches to supplier selection.
Koort, Hannes. "Room for More of Us? : Important Design Features for Informed Decision-Making in BIM-enabled Facility Management." Thesis, Uppsala universitet, Människa-datorinteraktion, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-447217.
Full textBarin, Alexandre. "Seleção de sistemas de geração de energia elétrica a partir de resíduos sólidos urbanos: uma abordagem com a lógica difusa." Universidade Federal de Santa Maria, 2012. http://repositorio.ufsm.br/handle/1/3668.
Full textSustainability is becoming a major driving force in energy policy, leading to the development of different strategies and projects. Many of these strategies are related to the application of novel methodologies for selecting Renewable Energy Systems (RES) and energy storage systems. Electrical generation with biogas from municipal solid waste (MSW) is one of the main alternatives to concern all the conceptions of sustainability - social, economic and environmental constrains. The complexity of sustainability and energy planning makes the multicriteria analysis a valuable tool for the decision making process. The use of an effective methodology for RES selection a decision making process is essential to guarantee the adequate energy management of the biogas and the MSW landfill. This methodology must be able to balance positive and negative aspects, achieving an overall solution that best satisfies the management needs. It is essential to deal with several parameters and concern the decision maker (DM) interaction over the decision making process. By applying the DM preferences into the development of the methodology, it is possible to corroborate the methodology outcome. The presented thesis will therefore develop a novel methodology for selection of RES fuelled by biogas from MSW landfills. This methodology taking as basis fuzzy multi-rules and multi-sets to provide an accurate analysis of conflicting aspects - operational, economic, environmental, social, etc. These aspects are taken into account for each study case according to different perspectives adopted by the DMs. The novel arrangements developed in this work are the creation of a previous classification of the priority criteria, the application of meta-rules and how to structure the fuzzy rules construction. The proposed arrangements have the purpose of easing the understanding of the methodology, as well as improving the DM interaction over the decision making process achieving in this way a better solution. This work presents the application of the novel decision making process to select the most appropriate energy source fuelled by biogas from MSW, considering the Caturrita II landfill located at Santa Maria City, Brazil. In conclusion, it is important to emphasize that the novel software may be used in any energy system selection, for supplying or storage, according to the analysis of several criteria and perspectives for each regional circumstances, as well as particular management needs..
A busca pelo desenvolvimento sustentável, em âmbitos sociais e ambientais, é um fator de extrema importância que incentiva a elaboração de várias pesquisas e projetos, como por exemplo, à aplicação de técnicas de gerenciamento e seleção de fontes alternativas renováveis de geração de energia. Dentre estas fontes, o aproveitamento energético do biogás resultante da decomposição de resíduos sólidos urbanos é um dos meios que propicia um desenvolvimento sustentável de forma mais completa. Para o devido aproveitamento de fontes alternativas renováveis, como a geração de energia elétrica e térmica a partir de resíduos sólidos urbanos, deve-se tomar como base métodos multicriteriais, considerando a existência de uma série de critérios para atender necessidades e interesses diversos quando se deseja selecionar tecnologias de geração e armazenamento de energia. A partir da utilização de métodos de ajuda a decisão é possível incorporar de forma clara as preferências dos agentes de decisão, obtendo como resposta final uma solução mais satisfatória e que pode ser corroborada através de validações heurísticas discussões dos resultados junto aos agentes de decisão. Mediante estes argumentos, o presente trabalho tem a finalidade de desenvolver uma metodologia de apoio a decisão para a seleção de sistemas para geração de energia elétrica com biogás proveniente de resíduos sólidos urbanos, avaliando devidamente cada processo decisório de acordo com aspectos econômicos, operacionais, ambientais e sociais. Para o alcance deste objetivo fez se uso da lógica difusa baseada em regras e conjuntos fuzzy aplicados sobre diversos critérios, avaliando diferentes perspectivas. Os aperfeiçoamentos mais importantes apresentados na elaboração desta tese se referem à criação de uma etapa de relevância prévia aos critérios em análise, criação e seleção de meta-regras e forma de apresentação e construção de tais regras, facilitando o entendimento dos agentes de decisão para a avaliação do processo decisório e propiciando uma maior participação dos mesmos para obtenção de um resultado mais satisfatório. É possível observar ainda que os aperfeiçoamentos desenvolvidos permitiram a devida construção e averiguação das modelagens construídas. No estudo de caso principal aterro sanitário Caturrita II localizado na cidade de Santa Maria é verificada a aplicabilidade da metodologia de ajuda a decisão desenvolvida visando a seleção da fonte de geração de energia elétrica mais apropriada a ser utilizada no aterro em questão. Por fim, deve-se enfatizar que a partir dos aperfeiçoamentos alcançados durante o desenvolvimento desta tese, foi possível construir uma metodologia de ajuda a decisão genérica que pode ser aplicada não somente na seleção de sistemas de geração de energia em aterros, mas também na seleção de quaisquer sistemas de geração e armazenamento de energia, desde que todos os aspectos envolvidos no processo decisório sejam devidamente incorporados no problema em questão.
Hsiao, Ya-Yun, and 蕭雅云. "Applying Fuzzy Multicriteria Decision-Making for Evaluating IS Outsourcing Alternatives." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/91218493372969659891.
Full text義守大學
資訊管理學系碩士班
95
Through the significant improvement of technology, the information technology keeps weeding through the old to bring fort the new. In order to go with the stream, increase operation efficiency, maintain the more complex information system availability, and update functions frequently, most corporations need the assistance from professional companies. To outsource the information system which is not the core ability of corporations, not only can reduce the costs of building system, but help corporations to focus on their particular field. Besides, choosing an appropriate contractor will raise the successful rate of outsourcing. Owing to the qualitative data and quantization data coexistent is unavoidable, and most of them are fuzziness and uncertainty. Therefore, this study planed to combine the Fuzzy Logic and the Fuzzy Multicriteria Decision-Making methods, which applies the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with fuzzy number and Fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (Fuzzy PROMETHEE) to have the best result of contractor evaluation. The case of selection for information system outsourcing in this study was evaluated by four decision-makers, and based on Linguistic Variable to give the weight of seven criteria which include the experience of contractor, the goodwill of contractor, the cooperative ability, technology skills, sustainable ability, and management ability of contractor, and general problems. Furthermore, according to criteria, the four candidature outsourcing contractors would be evaluated by linguistic variables. Additionally, depends on the Fuzzy Set Theory to carry on the set operation and de-fuzzify. Finally, obtains the rank of candidature outsourcing contractors. The application of FMCDM to evaluate the information system outsourcing contractor can be consequent on a common consensus at group decision making by rationalization and systematization, as efficient solve the lack of flexibility in the traditional FMCDM. The result of rank will provide the reference to the corporation which may need assistance of information system outsourcing to improve the efficiency.
Chen, Shi-Jay, and 陳士杰. "An Intelligent Fuzzy Multicriteria Decision Making System--Integrating Default Logic and Fuzzy Ranking Knowledge Base." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/38805924423543354493.
Full text朝陽大學
資訊管理系碩士班
87
Because the traditional multiple attribute decision methods have to request the crisp number from the decision maker which number is difficult to express the linguistic characteristic of the criteria or the weights. Therefore, many studies utilize fuzzy set theory in the application of decision making to resolve this problem. The decision method to handle fuzzy (non-crisp) criteria is hence called Fuzzy Multiple Attribute Decision Making (FMADM). Generally, the process of FMADM consists of two important parts : the fuzzy aggregation judgment and the fuzzy ranking method. In accordance with the FMADM, our research intends to solve the following problems. 1. Traditional fuzzy multi-attribute decision model is incapable of representing the default logic, i.e., the decision logic using informal criterion. In general, it is the major criteria determine the process result, however, second-order (minor) criteria after the process of the major criteria should also be considered and integrated into the model. 2. It is difficult to assign the proper weights for the informal criteria. 3. Each ranking method has its advantage and disadvantage and there is no general model to deal with various type of problems concerning with fuzzy ranking. Therefore, an intelligent system to help ranking fuzzy numbers is needed. We will integrate Yager''s method with second-order structure concept to handle the prioritized criteria. A fuzzy ranking rule base will be constructed to solve the ranking problem. Finally, we will implement an intelligent fuzzy system to support the traditional fuzzy multi-attribute decision model.
Ho, Chun-Yen, and 何俊彥. "Applying Fuzzy Multicriteria Decision-Making for Evaluating ERP System Development Methods and Implementation Strategies." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/42461480792311677969.
Full text義守大學
資訊管理學系碩士班
94
21 centuries is a new century that enterprises are facing a swift speed of changes. The Internet revolution has triggered the competition of utilizing time and space, that forcing enterprises have no choice but to squarely face such issues of global competition, division of labor among nations and the multinational operation. Thoroughly grasping information both inside and outside the organization and quickly adjusting the intension of organization may become the key point for breaking through siege to survive. In order to fulfill such needs, the implementation of ERP systems can be the cornerstone for enterprise’s sustainable development. Although many organizations have implementing various ERP systems, greatly parts of enterprises still be learning how to fully develop the capability of ERP systems, or even face embarrassing situation of failing the implementation. To probe these problems, many reasons related to the complexity of ERP systems, enterprise scales, business process, organization cultures and consulting firms. This research concentrates on the construction of the best implementing model of ERP system, reducing various risks and obstacles within the implementing process period, making enterprise take advantages of ERP systems. After collecting the ERP experts experience and standpoints by means of the questionnaire, this research applies the fuzzy multicriteria decision-making(FMCDM) to evaluate ERP systems development methods and implementation strategies, and further constructs the best model for enterprises to implement ERP systems in order to provide enterprises a reference resource for future implementing. In addition, because of realizing in the real decision environment that qualitative and quantitative data could not coexist and full of fuzziness and uncertainty, this research integrates fuzzy logic and multicriteria decision-making to develop Fuzzy VIKOR methodology and Fuzzy PROMETHEE methodology. Those methodologies can properly mediate the conflicts and contradictions during the decision-making process, effectively act in response to the lack of flexibility while adopting traditional multicriteria decision-making to deal with fuzzy problems and benefits in multicriteria group decision-making analysis for extensive application.
Pei-ChengChang and 張倍誠. "Developing the Performance Assessment System of Project Management Using Fuzzy Multicriteria Decision Making Approaches." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/86068699041080408830.
Full text國立成功大學
工業與資訊管理學系碩博士班
100
Project management is different from most aspects of business management and has attracted more and more attentions in firms. Moreover, there are currently many related software applications that can solve problems like scheduling and controlling. However, project management not only produces data, but also measures and analyzes the performance and the result of project execution. Based on obtained information and guidelines, decision makers can then plan projects more completely in the future. Conflicts between project goals often arise during project execution and how to trade off between goals in order to overcome such conflicts is often the most difficult task that project managers and project groups face. As a result, how to develop an effective method to measure project performance to aid in trade-off decisions is important issue in project management. In this study, we use fuzzy multicriteria decision making approaches to measure the performance of project management. First, we use the Fuzzy Analytic Network Process (FANP) which contains the concept of ex ante weight to develop the index and weights of dependent criteria, based on the subjective views of senior managers. We also use the concept of ex post weight to calculate the performance efficiency of projects using fuzzy data envelopment analysis. Finally, we analyze the results from these two different methods and develop the project performance assessment process. With the help of this feedback process, senior managers can better assign projects and achieve better results.
Books on the topic "Fuzzy multicriteria decision-making"
Pedrycz, Witold, Petr Ekel, and Roberta Parreiras. Fuzzy Multicriteria Decision-Making. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470974032.
Full textMarc, Roubens, ed. Fuzzy preference modelling and multicriteria decision support. Dordrecht: Kluwer Academic, 1994.
Find full textPedrycz, Witold. Models and algorithms of fuzzy multicriteria decision-making and their applications. Hoboken, NJ: John Wiley & Sons, 2011.
Find full textPedrycz, Witold, Petr Ekel, and Roberta Parreiras. Fuzzy Multicriteria Decision-Making: Models, Methods and Applications. Wiley & Sons, Limited, John, 2010.
Find full textPedrycz, Witold, Petr Ekel, and Roberta Parreiras. Fuzzy Multicriteria Decision-Making: Models, Methods and Applications. Wiley & Sons, Incorporated, John, 2011.
Find full textPedrycz, Witold, Petr Ekel, and Roberta Parreiras. Fuzzy Multicriteria Decision-Making: Models, Methods and Applications. Wiley & Sons, Incorporated, John, 2011.
Find full textMulticriteria Decision-Making under Conditions of Uncertainty: A Fuzzy Set Perspective. Wiley & Sons, Incorporated, John, 2020.
Find full textPedrycz, Witold, Petr Ekel, and Pereira Joel Jr. Multicriteria Decision-Making under Conditions of Uncertainty: A Fuzzy Set Perspective. Wiley & Sons, Incorporated, John, 2019.
Find full textPedrycz, Witold, Petr Ekel, and Joel Jr Pereira. Multicriteria Decision-Making under Conditions of Uncertainty: A Fuzzy Set Perspective. Wiley & Sons, Incorporated, John, 2019.
Find full textNishizaki, Ichiro, and Masatoshi Sakawa. Fuzzy and Multiobjective Games for Conflict Resolution. Physica, 2014.
Find full textBook chapters on the topic "Fuzzy multicriteria decision-making"
Carlsson, Christer, and Robert Fullér. "Fuzzy Multicriteria Decision Making." In Fuzzy Reasoning in Decision Making and Optimization, 65–99. Heidelberg: Physica-Verlag HD, 2002. http://dx.doi.org/10.1007/978-3-7908-1805-5_2.
Full textEl Alaoui, Mohamed. "Frequently Used Multicriteria Decision-Making Methods." In Fuzzy TOPSIS, 41–64. First edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9781003168416-4-4.
Full textFodor, János, and Marc Roubens. "Multiple criteria decision making." In Fuzzy Preference Modelling and Multicriteria Decision Support, 175–227. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-017-1648-2_7.
Full textZhukovin, Vladimir E. "A Fuzzy Multicriteria Decision Making Model." In Optimization Models Using Fuzzy Sets and Possibility Theory, 203–15. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3869-4_14.
Full textD’Apuzzo, Livia, Massimo Squillante, and Aldo G. S. Ventre. "Extending Aggregation Operators for Multicriteria Decision Making." In Multiperson Decision Making Models Using Fuzzy Sets and Possibility Theory, 98–104. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-2109-2_9.
Full textCables, E., M. T. Lamata, and J. L. Verdegay. "FRIM—Fuzzy Reference Ideal Method in Multicriteria Decision Making." In Soft Computing Applications for Group Decision-making and Consensus Modeling, 305–17. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60207-3_19.
Full textLavić, Zedina, and Sabina Dacić-Lepara. "Fuzzy Multicriteria Decision Making Model for HPP Alternative Selection." In Advanced Technologies, Systems, and Applications III, 62–69. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02574-8_6.
Full textZaychenko, Yuriy, and Helen Zaichenko. "Multicriteria Decision-Making Problems Under Uncertainty and Their Solution." In Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery, 1013–23. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32591-6_111.
Full textKahraman, Cengiz, Fatma Kutlu Gündoğdu, Ali Karaşan, and Eda Boltürk. "Advanced Fuzzy Sets and Multicriteria Decision Making on Product Development." In Studies in Systems, Decision and Control, 283–302. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42188-5_15.
Full textAtanassov, Krassimir, Evdokia Sotirova, and Velin Andonov. "Generalized Net Model of Multicriteria Decision Making Procedure Using Intercriteria Analysis." In Advances in Fuzzy Logic and Technology 2017, 99–111. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66830-7_10.
Full textConference papers on the topic "Fuzzy multicriteria decision-making"
Homenda, Wladyslaw, Agnieszka Jastrzebska, Witold Pedrycz, Fusheng Yu, and Yihan Wang. "Multicriteria Decision Making: Scale, Polarity, Symmetry, Interpretability." In 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2020. http://dx.doi.org/10.1109/fuzz48607.2020.9177705.
Full textAli, Rekik, Temani Moncef, and Ghedira Khaled. "Fuzzy model for multicriteria decision making." In 2014 Information and Communication Technologies Innovation and Application (ICTIA). IEEE, 2014. http://dx.doi.org/10.1109/ictia.2014.7883753.
Full textWani, M. F. "Tribomaterial Evaluation and Ranking Using Fuzzy Multicriteria Decision Making." In ASME 8th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2006. http://dx.doi.org/10.1115/esda2006-95732.
Full textDror-Rein, Elana, and Harvey B. Mitchell. "Fuzzy multicriteria decision making in the assignment problem." In Optical Science, Engineering and Instrumentation '97, edited by Oliver E. Drummond. SPIE, 1997. http://dx.doi.org/10.1117/12.279535.
Full textKong, Feng, Zhiguang Zhang, and Ying Liu. "Selection of Suppliers Based on Fuzzy Multicriteria Decision Making." In 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2008. http://dx.doi.org/10.1109/fskd.2008.52.
Full text"MULTICRITERIA DECISION MAKING IN BALANCED MODEL OF FUZZY SETS." In 4th International Conference on Informatics in Control, Automation and Robotics. SciTePress - Science and and Technology Publications, 2007. http://dx.doi.org/10.5220/0001620500400046.
Full textTom, Mary. "Computational intelligence using Fuzzy Multicriteria Decision Making for DIligenS: Dietary Intelligence System." In 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2012. http://dx.doi.org/10.1109/fuzz-ieee.2012.6250824.
Full textLe, Sun, Hai Dong, Farookh Khadeer Hussain, Omar Khadeer Hussain, Jiangang Ma, and Yanchun Zhang. "Multicriteria decision making with fuzziness and criteria interdependence in cloud service selection." In 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2014. http://dx.doi.org/10.1109/fuzz-ieee.2014.6891892.
Full textZeng-Tai Gong and Yan Ma. "Multicriteria fuzzy decision making method under interval-valued intuitionistic fuzzy environment." In 2009 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2009. http://dx.doi.org/10.1109/icmlc.2009.5212362.
Full textHongmei, Ju. "Multicriteria Fuzzy Decision-making Methods Based on Interval-valued Fuzzy Sets." In 2012 Fifth International Conference on Intelligent Computation Technology and Automation (ICICTA). IEEE, 2012. http://dx.doi.org/10.1109/icicta.2012.61.
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