Relevant bibliographies by topics / Fuzzy multicriteria decision-making

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Academic literature on the topic 'Fuzzy multicriteria decision-making'

Author: Grafiati
Published: 29 June 2021
Last updated: 21 June 2025

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Journal articles on the topic "Fuzzy multicriteria decision-making"

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Yager, Ronald R. "Multicriteria Decision-Making Using Fuzzy Measures." Cybernetics and Systems 46, no. 3-4 (2015): 150–71. http://dx.doi.org/10.1080/01969722.2015.1012884.

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Grabisch, Michel. "Fuzzy integral in multicriteria decision making." Fuzzy Sets and Systems 69, no. 3 (1995): 279–98. http://dx.doi.org/10.1016/0165-0114(94)00174-6.

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Wang, Hsiao-Fan. "Fuzzy multicriteria decision making—an overview." Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology 9, no. 1-2 (2000): 61–83. https://doi.org/10.3233/ifs-2000-119.

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Rolka, Leszek, Alicja Mieszkowicz-Rolka, and Grzegorz Drupka. "Multicriteria decision-making in flight route selection." Aircraft Engineering and Aerospace Technology 92, no. 9 (2020): 1377–84. http://dx.doi.org/10.1108/aeat-12-2019-0245.

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Purpose This paper aims to present a hybrid logical-arithmetic approach for selecting optimal flight routes. It can be used in the framework of free route airspace (FRA), which is aimed at achieving higher efficiency of air traffic management. Design/methodology/approach At the first stage, an initial subset of flight routes is selected that are promising alternatives with respect to single numerical criteria. At the second stage, a hybrid multicriteria decision model is constructed, consisting of numerical criteria and additional linguistic criteria. At the third stage, the numerical and linguistic criteria are integrated into a crisp decision matrix for determining the final ranking using the technique for order preferences by similarity to an ideal solution (TOPSIS) method. Findings The considered decision-making problem involves different kinds of criteria. Numerical (objective) criteria are given as real numbers. Linguistic (subjective) criteria are expressed with the help of fuzzy linguistic values. In consequence, a (logical) reasoning process prior to performing an (arithmetic) optimization procedure is necessary. Furthermore, a uniform optimization procedure requires a way of combining numerical and linguistic attributes. Practical implications The proposed approach can be applied to solving various multicriteria decision-making problems, where both objective and subjective criteria are taken into account. Originality/value First, a fuzzy information system that includes linguistic condition attributes is constructed. Second, a fuzzy inference system that is necessary for determining the resulting fuzzy criterion “turbulence conditions” for all flight routes is introduced. Finally, a way of combining numerical and linguistic criteria is proposed. This is done by converting values of fuzzy attributes into crisp ones, basing on the preferences of a decision-maker.
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Kahraman, Cengiz, Sezi Cevik Onar, and Basar Oztaysi. "Fuzzy Multicriteria Decision-Making: A Literature Review." International Journal of Computational Intelligence Systems 8, no. 4 (2015): 637–66. http://dx.doi.org/10.1080/18756891.2015.1046325.

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Zaychenko, 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.

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Satyadas, Antony, and H. C. Chen. "Multicriteria multigoal decision making - the fuzzy paradigm." Computers & Industrial Engineering 23, no. 1-4 (1992): 393–96. http://dx.doi.org/10.1016/0360-8352(92)90144-9.

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Ye, Jufeng. "Aggregation Operators of Trapezoidal Intuitionistic Fuzzy Sets to Multicriteria Decision Making." International Journal of Intelligent Information Technologies 13, no. 4 (2017): 1–22. http://dx.doi.org/10.4018/ijiit.2017100101.

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This paper presents the trapezoidal intuitionistic fuzzy weighted averaging (TIFWA) operator, trapezoidal intuitionistic fuzzy ordered weighted averaging (TIFOWA) operator, trapezoidal intuitionistic fuzzy weighted geometric (TIFWG) operator, and trapezoidal intuitionistic fuzzy ordered weighted geometric (TIFOWG) operator to aggregate the trapezoidal intuitionistic fuzzy information and investigates their properties. Furthermore, a multicriteria decision making method based on the TIFOWA and TIFOWG operators and the score function and accuracy function of a trapezoidal intuitionistic fuzzy number is established to deal with the multicriteria decision making problem with trapezoidal intuitionistic fuzzy information. Finally, an illustrative example demonstrates the application of the proposed method.
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Wibowo, Santoso, and Srimannarayana Grandhi. "Benchmarking knowledge management practices in small and medium enterprises." Benchmarking: An International Journal 24, no. 5 (2017): 1215–33. http://dx.doi.org/10.1108/bij-01-2016-0013.

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Purpose The purpose of this paper is to formulate the process of measuring and benchmarking the performance of knowledge management (KM) practices as a multicriteria group decision-making problem and present a new multicriteria group decision-making approach for effectively evaluating the performance of KM practices to meet the interests of various stakeholders in small and medium enterprises (SMEs). Design/methodology/approach A new multicriteria group decision-making approach is developed for evaluating the performance of KM practices of individual SMEs. Intuitionistic fuzzy numbers are used for representing the subjective assessments of decision makers in evaluating the relative importance of the evaluation criteria and the performance of individual KM practices with respect to specific evaluation criteria. A fuzzy multicriteria group decision-making algorithm is developed for measuring and benchmarking the performance of alternative KM practices. Findings The proposed multicriteria group decision-making approach is capable of effectively evaluating the performance of KM practices through adequately considering the presence of multiple decision makers, the multi-dimensional nature of the evaluation problem, and appropriately modeling the subjectiveness and imprecision of the evaluation process. The presentation of an example shows that the proposed fuzzy multicriteria group decision-making algorithm is simple to use and efficient in computation. Research limitations/implications The outcome of the multicriteria group decision-making approach is highly dependent on the inputs provided by the decision maker. Practical implications The novelty from this research lies in the utilization of a multicriteria group decision-making approach for evaluating the performance of KM practices in an organization. The outcome from the performance evaluation process allows the enterprise to adopt appropriate KM practices for achieving competitive advantages. Social implications The proposed multicriteria group decision-making approach has a significant social implication as it can be used as a decision-making tool for providing various decision makers in SMEs with useful and strategic information concerning the performance of KM practices in a given situation. Originality/value The originality of this paper lies in the development of the multicriteria group decision-making approach for effectively measuring and benchmarking the performance of KM practices of individual SMEs.
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Carnero, María Carmen. "Fuzzy Multicriteria Models for Decision Making in Gamification." Mathematics 8, no. 5 (2020): 682. http://dx.doi.org/10.3390/math8050682.

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Gamification is an innovative teaching technique that may prove hugely beneficial when properly used. For this reason, since 2002, the number of situations in which gamification is used has increased exponentially. This large number of options makes it difficult to choose the best application, especially in circumstances where there is the usual uncertainty that real-life decision making involves. To address this problem, this study creates two models, one using a fuzzy analytic hierarchy process (AHP), and the other, which combines fuzzy AHP with the measuring attractiveness by a categorical-based evaluation technique (MACBETH) approach, to choose the best gamification application for the ‘Operations Management’ course, within the Masters in Industrial Engineering. This is the first contribution in the literature combining fuzzy AHP and MACBETH. The decision centre used was the lecturer who teaches the course. There is no precedent in the literature using fuzzy logic to choose the best gamification application for a course. The results of the study show that Socrative is the best gamification application for this course within the Masters, and, as the models begin to be used in degree courses, the better choice would be Quizizz, the more clearly the earlier the course is taught within the degree programme.
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Dissertations / Theses on the topic "Fuzzy multicriteria decision-making"

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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.

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Continuous development has been occurring in the area of decision support systems. Modern systems focus on applying decision models that can provide intelligent support to the decision maker. These systems focus on modelling the human reasoning process in situations requiring decision. This task may be achieved by using an appropriate decision model. Multicriteria decision making (MCDM) is a common decision making approach. This research investigates and seeks a way to resolve various issues associated with the application of this model. MCDM is a formal and systematic decision making approach that evaluates a given set of alternatives against a given set of criteria. The global evaluation of alternatives is determined through the process of aggregation. It is well established that the aggregation process should consider the importance of criteria while determining the overall worth of an alternative. The importance of individual criteria and of sub-sets of the criteria affects the global evaluation. The aggregation also needs to consider the importance of the sub-set of criteria. Most decision problems involve dependent criteria and the interaction between the criteria needs to be modelled. Traditional aggregation approaches, such as weighted average, do not model the interaction between the criteria. Non-additive measures such as fuzzy measures model the interaction between the criteria. However, determination of non-additive measures in a practical application is problematic. Various approaches have been proposed to resolve the difficulty in acquisition of fuzzy measures. These approaches mainly propose use of past precedents. This research extends this notion and proposes an approach based on similarity-based reasoning. Solutions to the past problems can be used to solve the new decision problems. This is the central idea behind the proposed methodology. The methodology itself applies the theory of reasoning by analogy for solving MCDM problems. This methodology uses a repository of cases of past decision problems. This case base is used to determine the fuzzy measures for the new decision problem. This work also analyses various similarity measures. The illustration of the proposed methodology in a case-based decision support system shows that interactive models are suitable tools for determining fuzzy measures in a given decision problem. This research makes an important contribution by proposing a similarity-based approach for acquisition of fuzzy measures.
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Wagholikar, Amol S. "Acquisition of Fuzzy Measures in Multicriteria Decision Making Using Similarity-based Reasoning." Thesis, Griffith University, 2007. http://hdl.handle.net/10072/365403.

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Continuous development has been occurring in the area of decision support systems. Modern systems focus on applying decision models that can provide intelligent support to the decision maker. These systems focus on modelling the human reasoning process in situations requiring decision. This task may be achieved by using an appropriate decision model. Multicriteria decision making (MCDM) is a common decision making approach. This research investigates and seeks a way to resolve various issues associated with the application of this model. MCDM is a formal and systematic decision making approach that evaluates a given set of alternatives against a given set of criteria. The global evaluation of alternatives is determined through the process of aggregation. It is well established that the aggregation process should consider the importance of criteria while determining the overall worth of an alternative. The importance of individual criteria and of sub-sets of the criteria affects the global evaluation. The aggregation also needs to consider the importance of the sub-set of criteria. Most decision problems involve dependent criteria and the interaction between the criteria needs to be modelled. Traditional aggregation approaches, such as weighted average, do not model the interaction between the criteria. Non-additive measures such as fuzzy measures model the interaction between the criteria. However, determination of non-additive measures in a practical application is problematic. Various approaches have been proposed to resolve the difficulty in acquisition of fuzzy measures. These approaches mainly propose use of past precedents. This research extends this notion and proposes an approach based on similarity-based reasoning. Solutions to the past problems can be used to solve the new decision problems. This is the central idea behind the proposed methodology. The methodology itself applies the theory of reasoning by analogy for solving MCDM problems. This methodology uses a repository of cases of past decision problems. This case base is used to determine the fuzzy measures for the new decision problem. This work also analyses various similarity measures. The illustration of the proposed methodology in a case-based decision support system shows that interactive models are suitable tools for determining fuzzy measures in a given decision problem. This research makes an important contribution by proposing a similarity-based approach for acquisition of fuzzy measures.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>School of Information and Communication Technology<br>Full Text
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Caetani, 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.

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Este trabalho apresenta o processo de seleção de estratégia de reconversão industrial de uma pequena refinaria de petróleo no Sul do Brasil através da aplicação de uma modelagem integrada, utilizando um método multicriterial e programação matemática. Neste estudo foram identificadas linhas de negócio potencialmente aplicáveis à realidade da companhia e definido um conjunto de critérios de análise abrangendo as três dimensões da sustentabilidade empresarial: econômica, social e ambiental. Com base na avaliação da importância relativa de cada critério, atribuída por um grupo de decisores, e no desempenho das linhas de negócio em cada um dos critérios, foi aplicado método fuzzy TOPSIS para análise e ordenação das linhas de negócio. As informações resultantes desta análise, juntamente com dados econômicos objetivos, foram utilizadas em um modelo de programação linear inteira para avaliar portfólios viáveis de linhas de negócio, identificando estratégias candidatas à implementação na refinaria. O desempenho global de cada estratégia candidata, obtido mediante agregação dos desempenhos individuais das linhas de negócio e calculado conforme método fuzzy TOPSIS, foi analisado através de ferramentas gráficas, de modo a gerar elementos para subsidiar a seleção da melhor estratégia de reconversão. Os resultados obtidos demonstraram a eficiência da abordagem proposta, no sentido de facilitar o entendimento e a exploração da situação problema e, assim, oferecer um adequado suporte à tomada de decisão.<br>This 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.
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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.

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A group health insurance plan is an insurance plan that provides healthcare coverage to a selected group of people. In various countries, group health insurance plans are one of the major benefits offered through employers in the private sector. In recent years, the numbers of group health insurance plans offered in the market of health insurance have been increasing rapidly. This is due to compulsory government policies, which are imposed on employers in the private sector leading to an increasing demand for this insurance plan. Accordingly, employers may face a wide variety of available group health insurance plan alternatives. Despite the fact that employers in the private sector have a crucial and significant role in the health insurance market all over the world, little is known about how employers evaluate and choose group health insurance plans to cover their employees against the payments of benefits as a result of sickness or injury. Therefore, the primary concern in this research is to propose a model to assist employers within the private sector to evaluate alternative group health insurance plans and to select the most appropriate, in order to provide the perfect health care environment for their employees. In this research, a new hybrid Fuzzy Multiple Criteria Decision Making (MCDM) model is proposed for the selection problem. The proposed model tackles some issues that may be associated with the selection of the group health insurance plan, such as modelling uncertainty, studying the dependence among decision attributes, deriving decision attributes importance weights and ranking various alternatives. In the proposed hybrid model, four extension approaches based on the Fuzzy Delphi, Fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL), Fuzzy Group Prioritisation and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods are developed. Unlike the existing methods, the four proposed approaches, a new extended Fuzzy Delphi (FDE) method, a new extended Fuzzy DEMATEL method, a new Fuzzy Group Prioritisation (FGP) method and a new extended Fuzzy TOPSIS method, consider the importance weight of each member in group decision making since the selection problem needs evaluations from decision makers (DMs) with different levels of expertise and different perceptions. In the literature, there is some work on these methods, but to our knowledge, no research exists that combines these four methods. Moreover, the proposed model might be applied, due to its novelty, to any MCDM problem uncertainty in different. Furthermore, four new prototype decision support tools, termed Fuzzy Delphi Solver, Fuzzy DEMATEL Solver, Fuzzy Group Prioritisation Solver and Fuzzy TOPSIS Solver were developed in this study, based on the concepts of the four proposed approaches, in order to provide user-friendly interfaces for facilitating the application of these approaches. MATLAB software Version R2013a was adopted as a development environment for prototyping these new decision support tools in this study. The tools developed were validated internally by using hypothetical examples and checking the correctness of the results obtained by comparing them to other results generated from other software, such as Microsoft Excel or LINGO V13.0 software. In addition, a practical validation of the proposed hybrid Fuzzy MCDM model was investigated through conducting a case study of the Saudi health insurance industry. The main objectives of the case study were: 1) investigation of the evaluation process of selecting a group health insurance plan, including identifying the selection criteria and alternatives, studying the dependency issue, deriving the criteria weights, and ranking available alternatives; 2) application of the new decision support tools developed. In this case study, a group of nine DMs, Human Resources (HR) managers at nine different private companies in Saudi Arabia, were selected to take part of this case study. Their involvement achieved the first objective of the case study. At the end of the case study, a sensitivity analysis was conducted to indicate the robustness and the reliability of the results obtained. It is concluded that the proposed model is indeed beneficial. Finally, areas for further research were identified.
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Junior, 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/.

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A seleção de fornecedores tem impacto significante no custo e na qualidade de produtos manufaturados. Por isso, a seleção de fornecedores passou a ser vista como uma atividade bastante crítica para o desempenho da empresa compradora. Muitos estudos da literatura propõem o uso dos métodos multicritério fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) e fuzzy AHP (Analytic Hierarchy Process) para apoiar a seleção de fornecedores. Contudo, não são encontrados estudos que avaliem o desempenho destes métodos quando usados neste domínio de problema. Diante desta lacuna, este estudo compara os métodos fuzzy TOPSIS (CHEN, 2000) e fuzzy AHP (CHANG, 1996) no apoio à seleção de fornecedores. Esta pesquisa utiliza uma abordagem quantitativa descritiva empírica, baseada em modelagem e simulação. Os métodos fuzzy TOPSIS e fuzzy AHP foram aplicados em um caso ilustrativo de seleção de fornecedores. O desempenho dos fornecedores e o peso dos critérios foram avaliados por um especialista de uma empresa. Modelos de simulação foram implementados usando MATLAB® e aplicados na seleção de fornecedores de uma empresa de uma cadeia de suprimentos automotiva. Cinco fornecedores foram avaliados em relação à qualidade, custo, entrega, perfil e relacionamento. O peso dos critérios e o desempenho dos fornecedores foi avaliado por meio da opinião de um especialista da empresa. Posteriormente, os métodos fuzzy TOPSIS e fuzzy AHP foram comparados em relação à capacidade de apoiar a decisão em grupo, qualificação de fornecedores, escolha final de fornecedores, situações de compra e modelagem de decisões sob incerteza. A eficiência dos métodos em relação à complexidade computacional e à interação requerida com o usuário também foi comparada. Os resultados mostraram que o fuzzy TOPSIS é mais flexível e mais adequado que o fuzzy AHP para modelar diferentes tipos de cenários de seleção de fornecedores. A realização desta discussão é sugerida por Ertugrul e Karakasoglu (2008), e é relevante para ajudar pesquisadores e gestores na escolha de abordagens efetivas para lidar com diferentes cenários de seleção de fornecedores.<br>Supplier 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.
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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.

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Building Information Modeling (BIM) is becoming imperative across building disciplines to improve communication and workflow from the first blueprint. Maintenance and facility management is however lagging behind in adoption and research of BIM. Utilizing research-through-design, this study explores BIM-enabled facility management and the critical practice of decision-making at the Celsius building in Uppsala. Contextual design and inquiry were applied to identify and suggest important design features that support decisions related to the task of establishing maximum room occupation. Results show that facility managers can make use of fuzzy multicriteria decision-making and expert heuristics to independently reach conclusions. Important design features were found to heavily rely on the existing building models, where context-view filtered to room capacity data in the existing BIM-system effectively supported the users’ assessment of data. The filtered, aggregated information presented in a simplified mobile format was insufficient for decision-making, suggesting that the building model was more important than initially perceived.
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Barin, 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.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico<br>Sustainability 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..<br>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.
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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.

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碩士<br>義守大學<br>資訊管理學系碩士班<br>95<br>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.
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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.

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碩士<br>朝陽大學<br>資訊管理系碩士班<br>87<br>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.
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Wang, Chih-huang, and 王志煌. "New Methods for Handling Fuzzy Risk Analysis Problems and Prioritized Multicriteria Decision Making Problems." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/97d57z.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>95<br>In this thesis, we present a new approach for fuzzy risk analysis based on the ranking of fuzzy numbers. First, we present a new method for ranking fuzzy numbers using the α-cuts, the belief features and the signal/noise ratios of fuzzy numbers. The proposed method can overcome the drawbacks of some existing methods for ranking fuzzy numbers. Then, we apply the proposed fuzzy ranking method to present a fuzzy risk analysis algorithm to deal with fuzzy risk analysis problems. The proposed fuzzy risk analysis algorithm can provide a useful way to deal with fuzzy risk analysis problems. In this thesis, we also present a new method for prioritized multicriteria decision making, where the weights of the lower priority criteria of each alternative depends on whether each alternative satisfies the requirements of all the higher priority criteria or not. If the requirements of all the higher priority criteria can not be satisfied by the alternative, then the weights of the lower priority criteria are all zero. That is, the degrees of satisfaction with respect to the lower priority criteria do not affect the overall degree of satisfaction. Furthermore, we present a generalized prioritized multicriteria decision making method for handling multicriteria decision making problems in which some criteria may have equal priority and the criteria with equal priority are aggregated by using the ordered weighted averaging (OWA) operator or the weighted averaging method. The proposed methods can overcome the drawbacks of the Yager’s methods. The proposed generalized multicriteria decision making method can handle multicriteria decision making problems in a more intelligent and more flexible manner.
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Books on the topic "Fuzzy multicriteria decision-making"

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Pedrycz, Witold, Petr Ekel, and Roberta Parreiras. Fuzzy Multicriteria Decision-Making. John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470974032.

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Pedrycz, Witold. Models and algorithms of fuzzy multicriteria decision-making and their applications. John Wiley & Sons, 2011.

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Pedrycz, Witold, Petr Ekel, and Roberta Parreiras. Fuzzy Multicriteria Decision-Making. Wiley & Sons, Incorporated, John, 2010.

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Roubens, M. R., and J. C. Fodor. Fuzzy Preference Modelling and Multicriteria Decision Support. Springer London, Limited, 2013.

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Fuzzy Preference Modelling and Multicriteria Decision Support. Springer Netherlands, 2010.

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Pedrycz, Witold, Petr Ekel, and Roberta Parreiras. Fuzzy Multicriteria Decision-Making: Models, Methods and Applications. Wiley & Sons, Incorporated, John, 2011.

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Pedrycz, Witold, Petr Ekel, and Roberta Parreiras. Fuzzy Multicriteria Decision-Making: Models, Methods and Applications. Wiley & Sons, Limited, John, 2010.

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Pedrycz, Witold, Petr Ekel, and Roberta Parreiras. Fuzzy Multicriteria Decision-Making: Models, Methods and Applications. Wiley & Sons, Incorporated, John, 2011.

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Pedrycz, Witold, Petr Ekel, and Roberta Parreiras. Fuzzy Multicriteria Decision-Making: Models, Methods and Applications. Wiley & Sons, Limited, John, 2010.

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Pedrycz, Witold, Petr Ekel, and Joel Jr Pereira. Multicriteria Decision-Making under Conditions of Uncertainty: A Fuzzy Set Perspective. Wiley & Sons, Incorporated, John, 2019.

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Book chapters on the topic "Fuzzy multicriteria decision-making"

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Carlsson, Christer, and Robert Fullér. "Fuzzy Multicriteria Decision Making." In Fuzzy Reasoning in Decision Making and Optimization. Physica-Verlag HD, 2002. http://dx.doi.org/10.1007/978-3-7908-1805-5_2.

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El Alaoui, Mohamed. "Frequently Used Multicriteria Decision-Making Methods." In Fuzzy TOPSIS. CRC Press, 2021. http://dx.doi.org/10.1201/9781003168416-4-4.

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Fodor, János, and Marc Roubens. "Multiple criteria decision making." In Fuzzy Preference Modelling and Multicriteria Decision Support. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-017-1648-2_7.

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Zhukovin, Vladimir E. "A Fuzzy Multicriteria Decision Making Model." In Optimization Models Using Fuzzy Sets and Possibility Theory. Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3869-4_14.

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Mohanty, Anita, Ambarish G. Mohapatra, Subrat Kumar Mohanty, and Abhijit Mohanty. "Fuzzy Systems for Multicriteria Optimization." In Multi-Criteria Decision-Making and Optimum Design with Machine Learning. CRC Press, 2024. http://dx.doi.org/10.1201/9781032635170-2.

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D’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. Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-2109-2_9.

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Lavić, Zedina, and Sabina Dacić-Lepara. "Fuzzy Multicriteria Decision Making Model for HPP Alternative Selection." In Advanced Technologies, Systems, and Applications III. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02574-8_6.

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Cables, 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. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60207-3_19.

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Zaychenko, Yuriy, and Helen Zaichenko. "Multicriteria Decision-Making Problems Under Uncertainty and Their Solution." In Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32591-6_111.

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Kahraman, 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. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42188-5_15.

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Conference papers on the topic "Fuzzy multicriteria decision-making"

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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.

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Ali, 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.

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Wani, 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.

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A procedure based on fuzzy multicriteria decision making is developed for evaluation and ranking of tribomaterials. Tribomaterial properties which influence performance of triboelements at operational stage are considered as criteria for evaluation of tribomaterial. Tribomaterial properties, weighting factors and desired values are converted into fuzzy membership functions called trapezoidal fuzzy numbers. Tribomaterial ranking index is evaluated from weighted fuzzy tribomaterial suitability value for various degrees of optimism through a series of fuzzy arithmetic operations. Higher the value of index better is ranking of tribomaterial. A step by step procedure for evaluation and ranking of tribomaterial is suggested. An example of plain bearing has been presented for illustration of the procedure.
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Dror-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.

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Kong, 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.

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Le, 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.

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Tom, 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.

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"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.

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Zeng-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.

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Hongmei, 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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