Relevant bibliographies by topics / Fuzzy TOPSIS

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Academic literature on the topic 'Fuzzy TOPSIS'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 September 2023

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Journal articles on the topic "Fuzzy TOPSIS"

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ZENG, Shouzhen, and Yao XIAO. "A METHOD BASED ON TOPSIS AND DISTANCE MEASURES FOR HESITANT FUZZY MULTIPLE ATTRIBUTE DECISION MAKING." Technological and Economic Development of Economy 24, no. 3 (May 18, 2018): 969–83. http://dx.doi.org/10.3846/20294913.2016.1216472.

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The aim of this paper is to provide a methodology to hesitant fuzzy multiple attribute decision making using technique for order preference by similarity to ideal solution (TOPSIS) and distance measures. Firstly, the inadequacies of the existing hesitant fuzzy TOPSIS method are analyzed in detail. Then, based on the developed hesitant fuzzy ordered weighted averaging weighted aver-aging distance (HFOWAWAD) measure, a modified hesitant fuzzy TOPSIS, called HFOWAWAD-TOPSIS is introduced for hesitant fuzzy multiple attribute decision making problems. Moreover, the advantages and some special cases of the HFOWAWAD-TOPSIS are presented. Finally, a numerical example about energy policy selection is provided to illustrate the practicality and feasibility of the developed approach.
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Zeng, Shouzhen, and Yao Xiao. "TOPSIS method for intuitionistic fuzzy multiple-criteria decision making and its application to investment selection." Kybernetes 45, no. 2 (February 1, 2016): 282–96. http://dx.doi.org/10.1108/k-04-2015-0093.

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Purpose – The purpose of this paper is to present a hybrid intuitionistic fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method, called intuitionistic fuzzy ordered weighted averaging weighted averaging (OWAWA) distance TOPSIS (IFOWAWAD-TOPSIS) method for intuitionistic fuzzy multiple-criteria decision making (MCDM) problems. Design/methodology/approach – Based on the OWAWA operator, the authors develop the intuitionistic fuzzy OWAWA distance measure, then the IFOWAWAD-TOPSIS method is obtained by using the IFOWAWAD and traditional TOPSIS. Findings – The developed IFOWAWAD-TOPSIS method can overcome the drawback of traditional TOPSIS method that cannot consider both the subjective information of attributes and the attitudinal character of decision maker. Research limitations/implications – Clearly, this paper is devoted to the OWA operator, MCDM and intuitionistic fuzzy theory. Practical implications – The developed method is applicable in a wide range of situations such as decision-making, statistics, engineering and economics. A numerical example concerning investment selection is given to illustrate the practicability and usefulness of the proposed approach. Originality/value – This paper fulfils an identified need to study how to make a decision considering both the subjective information of attribute and the attitudinal character of decision maker in intuitionistic fuzzy environment.
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Liu, Chiun-Ming, Mei-Yu Ji, and Wen-Chieh Chuang. "Fuzzy TOPSIS for Multiresponse Quality Problems in Wafer Fabrication Processes." Advances in Fuzzy Systems 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/496158.

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The quality characteristics in the wafer fabrication process are diverse, variable, and fuzzy in nature. How to effectively deal with multiresponse quality problems in the wafer fabrication process is a challenging task. In this study, the fuzzy technique for order preference by similarity to an ideal solution (TOPSIS), one of the fuzzy multiattribute decision-analysis (MADA) methods, is proposed to investigate the fuzzy multiresponse quality problem in integrated-circuit (IC) wafer fabrication process. The fuzzy TOPSIS is one of the effective fuzzy MADA methods for dealing with decision-making problems under uncertain environments. First, a fuzzy TOPSIS methodology is developed by considering the ambiguity between quality characteristics. Then, a detailed procedure for the developed fuzzy TOPSIS approach is presented to show how the fuzzy wafer fabrication quality problems can be solved. Real-world data is collected from an IC semiconductor company and the developed fuzzy TOPSIS approach is applied to find an optimal combination of parameters. Results of this study show that the developed approach provides a satisfactory solution to the wafer fabrication multiresponse problem. This developed approach can be also applied to other industries for investigating multiple quality characteristics problems.
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Kaaffah, Faiz Muqorrir, and Handry Eldo. "STUDI PERBANDINGAN METODE FUZZY AHP DAN FUZZY TOPSIS DALAM SISTEM PENDUKUNG KEPUTUSAN UNTUK PENENTUAN INVESTASI TERBAIK." BULLETIN OF NETWORK ENGINEER AND INFORMATICS 1, no. 2 (October 1, 2023): 60. http://dx.doi.org/10.59688/bufnets.v1i2.14.

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Penelitian ini membandingkan metode Fuzzy AHP dan Fuzzy TOPSIS dalam sistem pendukung keputusan untuk penentuan investasi terbaik. Dataset investasi dengan kriteria ROI, Risiko Investasi, Waktu Pengembalian Modal, dan NPV digunakan. Dalam Fuzzy AHP, dilakukan perbandingan pasangan kriteria untuk mendapatkan bobot kriteria. Dalam Fuzzy TOPSIS, dihitung nilai preferensi berdasarkan jarak relatif positif dan negatif. Hasil penelitian menunjukkan bahwa kedua metode memberikan wawasan berharga dalam pengambilan keputusan investasi. Fuzzy AHP memberikan bobot kriteria yang akurat, sementara Fuzzy TOPSIS memberikan peringkat alternatif berdasarkan perbedaan relatif dengan solusi ideal. Penggunaan kedua metode ini secara bersama-sama dapat memberikan informasi yang komprehensif dan dapat diandalkan untuk memilih investasi terbaik. Penelitian ini memberikan kontribusi dalam memperluas pemahaman tentang penggunaan metode Fuzzy AHP dan Fuzzy TOPSIS dalam konteks investasi, yang dapat menjadi acuan bagi pengambil keputusan dalam memilih metode yang sesuai dengan kebutuhan mereka.
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Yavuz, V. Alpagut. "An Analysis of Job Change Decision Using a Hybrid Mcdm Method: A Comparative Analysis." International Journal of Business and Social Research 6, no. 3 (April 15, 2016): 60. http://dx.doi.org/10.18533/ijbsr.v6i3.935.

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<p>This paper investigates the decision process relating to job change which mostly depends on individual’s expectations about a job. Failing to fully understand the factors shaping these expectations leads to dissatisfaction and poor work performance; which produces unwanted consequences for both individuals and businesses. Since job change decision is defined as a multiple criteria decision making (MCDM) problem. This study uses a hybrid approach as a methodology combining fuzzy Analytic Hierarchy Analysis (AHP) and fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) for the job change decision of a faculty working in a university. In this approach, while the use of fuzzy AHP method helps determine the weight of the decision criteria; fuzzy TOPSIS enables the evaluation of the alternatives. In order to investigate the methods’ applicability in multiple dimensions of decision problem space, a comparison analysis is conducted with the three methodologies; fuzzy AHP, fuzzy TOPSIS and the proposed hybrid approach (named fuzzy AHP-TOPSIS) in the same decision making context. Four factors are considered for the comparison: adequacy to changes of criteria or alternatives; agility in the decision process; computational complexity; and the number of criteria and alternatives. Analysis shows that three methods achieve the same results. This verifies their robustness and indicates that MCDM methods are viable in job change decisions. However; comparison analysis shows that based on the four factors; the proposed hybrid fuzzy AHP-TOPSIS method provide more consistent results than fuzzy AHP and fuzzy TOPSIS methods. Thus the proposed hybrid fuzzy AHP-TOPSIS method is more appropriate to use on a wide range of job change decision problems.</p>
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Chou, Ying-Chyi, Hsin-Yi Yen, Van Thac Dang, and Chia-Chi Sun. "Assessing the Human Resource in Science and Technology for Asian Countries: Application of Fuzzy AHP and Fuzzy TOPSIS." Symmetry 11, no. 2 (February 17, 2019): 251. http://dx.doi.org/10.3390/sym11020251.

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The fuzzy analytic hierarchy process (AHP) and fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are extremely beneficial when a decision-making process is complex. The reason is that AHP and TOPSIS can prioritize multiple-choice criteria into a hierarchy by assessing the relative importance of criteria and can thus generate an overall ranking of the alternatives. This study uses fuzzy AHP and fuzzy TOPSIS to evaluate the human resource in science and technology (HRST) performance of Southeast Asian countries. The fuzzy TOPSIS analysis indicates that Singapore, South Korea, and Taiwan have similarities in their desired levels of HRST performance. That is, these three countries have better HRST performances than other Southeast Asian countries.
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He, Yuan Yuan, and Zai Wu Gong. "A Method to Extend TOPSIS for Fuzzy Multiple Attribute Decision Making." Advanced Materials Research 634-638 (January 2013): 3936–39. http://dx.doi.org/10.4028/www.scientific.net/amr.634-638.3936.

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The TOPSIS method is developed for solving the problem of fuzzy multiple attribute decision making, in which the attribute values take the form of triangular fuzzy numbers. A new distance for triangular fuzzy numbers is introduced to measure difference between two alternatives. And we apply the similarity degree derived from the new fuzzy distance to design a model of TOPSIS. Then, we utilize the TOPSIS method to aggregate the fuzzy information corresponding to each alternative, and rank the alternatives according to their relative closeness. Finally, an illustrative example is given to demonstrate the proposed approach practicality and effectiveness.
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Fahmi, Aliya, Fazli Amin, Saleem Abdullah, and Asad Ali. "Approaches to Multi-Attribute Group Decision-Making Based on Trapezoidal Linguistic Uncertain Cubic Fuzzy TOPSIS Method." New Mathematics and Natural Computation 15, no. 02 (June 20, 2019): 261–82. http://dx.doi.org/10.1142/s1793005719500145.

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In this paper, we describe the new idea of trapezoidal linguistic uncertain cubic fuzzy number. We discuss some basic operational laws of trapezoidal linguistic uncertain cubic fuzzy number and hamming distance of TrLUCFNs. We introduce the new concept of trapezoidal linguistic uncertain cubic fuzzy TOPSIS method. Furthermore, we extend the classical trapezoidal linguistic uncertain cubic fuzzy TOPSIS method to solve the MCDM method based on trapezoidal linguistic uncertain cubic fuzzy TOPSIS method. The new ranking method for TrLUCFNs is used to rank the alternatives. Finally, an illustrative example is given to verify and prove the practicality and effectiveness of the proposed method.
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Izdhihar, Fairuz Nadhif, Evawati Alisah, and Abdussakir Abdussakir. "Metode Fuzzy TOPSIS Sebagai Sistem Pendukung Keputusan dalam Menentukan Pegawai Berprestasi." Jurnal Riset Mahasiswa Matematika 2, no. 6 (September 1, 2023): 233–46. http://dx.doi.org/10.18860/jrmm.v2i6.22024.

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Fuzzy TOPSIS as a decision support system is a mathematical method with the best alternative concept chosen not only to have the shortest distance to the positive ideal solution, but also to have the longest distance to the negative ideal solution. The use of Fuzzy TOPSIS as a decision support system can minimize the weaknesses that exist in the TOPSIS method. The purpose of this study is to apply the Fuzzy TOPSIS method as a Decision Support System (SPK) to determine outstanding employees at the Batu City Population and Civil Registration Office. The Human Resources (HR) Division has the task of validating the value and processing the value of employee work goals and work behavior using the Fuzzy TOPSIS implementing into recommendations for outstanding employees. Data processing is carried out fuzzy, while calculations are carried out by the TOPSIS method. The output of this calculation is in the form of ranking the value of preferences and recommendations available for all employees. The calculation results obtained the highest preference value, namely by the first alternative with a value of 1. The alternative occupied a position as an outstanding employee at the Batu City Population and Civil Registration Office.
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Kar, Mr UditNarayan, and Miss Arunima Kar. "EVALUATING PARETO FRONT WITH TOPSIS AND FUZZY TOPSIS FOR LITERACY RATES IN ODISHA." EPH - International Journal of Science And Engineering 1, no. 4 (December 27, 2015): 18–32. http://dx.doi.org/10.53555/eijse.v1i4.96.

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In engineering design and manufacturing, conflicting disciplines and technologies are always involved in the design process. Decision making is the process of finding the best option among the feasible alternatives. Multi Criteria Decision Making (MCDM) methods can help decision makes to effectively deal with such situation and make wise design decision to produce an optimized design. There are varieties of existing MCDM methods, thus the selection of the most appropriate method is critical since the use of inappropriate methods often causes misleading decision process. The MCDM methods are based on aggregating function representing closeness to ideal, TOPSIS is one of the most efficient methods. And also it can be fuzziffied which gives rise to a new method called Fuzzy TOPSIS. Fuzzy TOPSIS is a new method for MCDM and very easy to understand and it is originated in the compromise programming method. Here we have adapted the Fuzzy TOPSIS method and we have arranged the multiple numbers of criteria using Knapsack algorithm and Pareto Front with the help of non dominated sorting method. Then we have ranked all the alternatives with classical Fuzzy TOPSIS method. In this paper the literacy rate of Odisha (a state of India) has been analyzed by using normal TOPSIS and fuzzy TOPSIS methods and the comparative results are given. The data sets considered in this paper are the real time data given by National Census (20002013).
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Dissertations / Theses on the topic "Fuzzy TOPSIS"

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Pokorný, Tomáš. "Využití teorie fuzzy množin a jejich rozšíření v metodě TOPSIS." Master's thesis, Vysoká škola ekonomická v Praze, 2016. http://www.nusl.cz/ntk/nusl-205686.

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This master's thesis deals with extensions of TOPSIS method, which is one of methods for multi-criteria evaluation of alternatives. These extensions use theory of fuzzy sets (FS) and their futher extensions to interval-valued (IVFS), intuitionistic (IFS) and hesitant (HFS) fuzzy sets and their combinations (IVIFS, IVIHFS). Significant part of this thesis explains the principle of fuzzy sets and their generalizations. Descriptions of operators for aggregations of grades of membership has very important role here. Next, very short description of multi-criteria evaluation problems and detailed description of TOPSIS method are contained. The second half of this thesis is dedicated to four existing extensions of TOPSIS metod that uses theories of FS, IVFS, IVIFS and IVIHFS. Every method is illustrated with an example that shows principle of calculations. It illustrates new possibilities of the methods that use new sets theories and potential complications and deviations from the original TOPSIS method. At the end of this thesis, evaluation of usefulness of used approaches is mentioned.
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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.
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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Arif-Uz-Zaman, Kazi. "A fuzzy TOPSIS based multi criteria performance measurement model for lean supply chain." Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/63710/1/Kazi_Arif-Uz-Zaman_Thesis.pdf.

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Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.
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MARTINS, GUILHERME DE ANDRADE. "FUZZY AHP-TOPSIS MODEL FOR THE ASSESSMENT AND SELECTION OF RENEWABLE ENERGY GENERATION TECHNOLOGIES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=32222@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO
A avaliação e seleção de tecnologias de geração de energia elétrica a partir de fontes renováveis visa melhorar a eficiência nas decisões de expansão dos sistemas elétricos em geral, elencando tecnologias mais adequadas em função de seus impactos ambientais, sociais, econômicos, técnicos e políticos. Os processos decisórios referentes à escolha de tecnologias de geração de energia caracterizam-se por subjetividade, incerteza e ambiguidade. Os métodos multicritério de apoio à decisão, combinados com a lógica dos conjuntos fuzzy constituem uma alternativa adequada para a modelagem de avaliação e seleção de tecnologias em ambientes sob incerteza. O objetivo principal desta dissertação é propor um modelo de avaliação e seleção de tecnologias para geração de energia elétrica a partir de fontes renováveis, com o auxílio de métodos multicritério fuzzy de apoio à decisão. A pesquisa pode ser considerada aplicada, descritiva e metodológica. Quanto aos meios de investigação, a metodologia compreende pesquisa bibliográfica e documental; pesquisa experimental, com a aplicação de métodos multicritério fuzzy de apoio à decisão para hierarquização de alternativas tecnológicas de energia elétrica a partir de fontes renováveis; e desenvolvimento de um estudo empírico no Estado do Rio de Janeiro. Destacam-se como resultados a seleção de tecnologias mais adequadas em função de seus impactos ambientais, sociais, econômicos, técnicos e políticos e a demonstração da aplicabilidade do modelo proposto. No caso do Estado do Rio de Janeiro, a tecnologia que se mostrou mais adequada, dado potencial de fontes renováveis, foi a solar fotovoltaica.
Assessment and selection of renewable energy generation technologies addresses to improve efficiency in electrical system expansion decisions, by selecting technologies that are more appropriate considering some criteria, like environmental, social, economic, technical and political. The decision-making processes regarding the choice of energy generation technologies are characterized by subjectivity, uncertainty and ambiguity. Multicriteria decision support method, combined with fuzzy logic, is an adequate alternative for measuring and evaluating the performance of technologies in environment under uncertainty. The main aim of this dissertation is to propose a model for selection the performance of technologies for electric power generation from renewable sources, with the support of multicriteria fuzzy decision-making methods. The research can be considered applied, descriptive and methodological. As for means of investigation, the methodology comprises bibliographical and documentary research; Experimental research, with the application of multicriteria fuzzy decision-making methods for hierarchization of technologies for electric power generation alternatives from renewable sources; and development of an empirical study in the State of Rio de Janeiro. The results highlight the selection of the most appropriate technologies according to their environmental, social, economic, technical and political impacts and the demonstration of the applicability of the proposed model. In the case of the State of Rio de Janeiro, the most appropriate technology, given the potential of renewable sources, was solar photovoltaic.
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Yaakob, Abdul Malek Bin. "Multi criteria decision making methodology for fuzzy rule based systems and networks using TOPSIS." Thesis, University of Portsmouth, 2017. https://researchportal.port.ac.uk/portal/en/theses/multi-criteria-decision-making-methodology-for-fuzzy-rule-based-systems-and-networks-using-topsis(8efb475a-4f98-4d5c-846d-f01b01328dda).html.

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Fuzzy systems and networks are vital within the armoury of fuzzy tools and applicable to real life decision making environments. Three types of fuzzy systems introduced in literatures which are systems with single rule base, systems with multiple rule bases and system with networked rule bases. This research introduces novel extension of the Technique of Ordering of Preference by Similarity to Ideal Solution (TOPSIS) methods and uses fuzzy systems and networks to solve multi-criteria decision making problems where both benefit and cost are presented as subsystems. In conjunction, the implementation of fuzzy sets type-1, type-2 and Z-number of proposed approaches is also presented. Furthermore, literatures have observed that tracking the performance of criteria is crucial by controlling the estimation of uncertainty of the criteria. Thus, the decision maker evaluates the performance of each alternative and further observes the performance for both benefit and cost criteria. This research improves significantly the transparency of the TOPSIS methods while ensuring higher effectiveness in comparison to established approaches. Ensuring the practicality and the effectiveness of proposed methods in a realistic scenario, the problem of ranking traded stock is studied. This case study is conducted based on stocks traded in a developing financial market such as Kuala Lumpur Stock Exchange. The ranking based on proposed methods is validated comparatively using performance indicators such as Spearman Rho correlation, Kendall Tau correlation, Root Mean Square Errror and Average Absolute Distance by assuming ranking based on return on investment as a benchmarking. Based on the case study, the proposed methods outperform the established TOPSIS methods in term of average rank position.
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Jaffal, Hussein, and Cheng Tao. "Multiple Attributes Group Decision Making by Type-2 Fuzzy Sets and Systems." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2659.

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We are living in a world full of uncertainty and ambiguity. We usually ask ourselves questions that we are uncertain about their answers. Is it going to rain tomorrow? What will be the exchange rate of euro next month? Why, where and how should I invest? Type-1 Fuzzy sets are characterized by the membership function whose value for a given element x is said to be the grade of membership having a value in the interval [0, 1]. In addition, type-1 fuzzy sets have limited capabilities to deal with uncertainty. In our thesis, we study another concept of a fuzzy description of uncertainty which is called Type-2 fuzzy sets. According to this concept, for any given element x, we can’t speak of an unambiguously specified value of the membership function. Moreover, Type-2 fuzzy sets constitute a powerful tool for handling uncertainty. The aim of our thesis is to examine the potential of the Type-2 fuzzy sets especially in decision making. So, we present basic definitions concerning Type-2 fuzzy sets, and operations on these sets are to be discussed too. Then, Type-2 fuzzy relations and methods of transformation of Type-2 fuzzy sets will be introduced. Also, the theory of Type-2 Fuzzy sets will serve for the construction of the fuzzy inference system. Finally, we utilize interval type-2 fuzzy sets in the application of Multiple Attributes Group Decision Making which is called TOPSIS.
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Madi, Elissa Nadia. "An improved uncertainty in multi-criteria decision making model based on type-2 fuzzy TOPSIS." Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/55394/.

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This thesis presents a detailed study about one of the Multiple Criteria Decision Making (MCDM) models, namely Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), based on fuzzy set theory (FST) by focusing on improving modelling uncertain information provided by a group of decision makers (DMs). An exploration of issues and limitations in current models of standard TOPSIS and fuzzy TOPSIS were made. Despite many variations of type-1 fuzzy TOPSIS (T1-TOPSIS) model, none of the studies explaining the details of the key stages of standard TOPSIS (non-fuzzy) and T1-TOPSIS are based on a step-wise procedure. A detailed study was conducted which involve the process of identifying the limitations of standard TOPSIS and T1-TOPSIS. Based on this, a novel contribution on the comparison between these two models in systematic stepwise procedure was given. This study successfully identified and discussed the limitations, issues and challenges which have not been investigated sufficiently in the context of T1-TOPSIS model. Based on this exploration, further investigation of multiple variants of the extension of the fuzzy TOPSIS model for solving the MCDM problem was made with the primary aim of detailing the steps involved. One challenge that has risen is that it is not straightforward to differentiate between the multiple variants of TOPSIS existing today. A systematic comparison was made between standard T1-TOPSIS model with the recently extended model to show the differences between both models and to provide context for their respective strengths and limitations both in the complexity of application and expressiveness of results. Based on the resulting comparison, the differences in the steps implemented by these two Fuzzy TOPSIS models were highlighted throughout the worked example. Furthermore, this task highlights the ability of both models to handle different levels of uncertainty. Following the exploration of issues and limitations of the current model, as well as a comparative study, a novel extension of type-2 fuzzy TOPSIS model is proposed in this thesis which suggests providing an interval-valued output to reflect the uncertainties and to model subjective information. The proposed model enables to uniquely captures input uncertainty (i.e., decision-makers' preferences) in the decision-making outputs and provide a direct mapping of uncertainty in the inputs to outputs. By keeping the output values in interval form, the proposed model reduces the loss of information and maximises the potential benefit of using Interval Type-2 Fuzzy Sets (IT2 FSs). To demonstrate the MCDM problems when a various level of uncertainty is introduced, a novel experimental method was proposed in this study. The primary aim is to explore the use of IT2 FSs in handling uncertainty based on the TOPSIS model. This experiment was conducted to show how the variation of uncertainty levels in the input affects the final outputs. An implementation of the proposed model to two different case studies was conducted to evaluate the proposed model. The proposed model for the first time generates an interval-valued output. As intervals can, for example, exhibit partial overlap, a novel extended measure is proposed to compare the resulting interval-valued output from various cases (i.e., overlapping and non-overlapping) of the interval with considering uncertainty.
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Martins, Patrícia Maria dos Santos. "Modelo de decisão para avaliar a utilização sustentável das tecnologias de informação." Master's thesis, Faculdade de Ciências e Tecnologia, 2012. http://hdl.handle.net/10362/8061.

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Dissertação para obtenção do grau de Mestre em Engenharia e Gestão Industrial
Com os crescentes problemas associados ao elevado consumo energético e à emissão de poluentes para a atmosfera, as preocupações em torno da sustentabilidade ganham uma dimensão considerável. Aproximadamente 2% destas emissões são provocadas pelo setor das tecnologias de informação. Os parâmetros associados ao green IT são uma ferramenta com a capacidade de controlar e reduzir a pegada de carbono provocada pelas tecnologias de infor-mação, supondo a adoção de iniciativas sustentáveis ao longo do ciclo de vida de um equipa-mento. No contexto empresarial, com o aumento da utilização das TIC, o consumo de energia aumen-ta gradualmente e as opiniões relativamente ao green IT dividem-se. Enquanto algumas em-presas defendem que as práticas sustentáveis estão fora dos seus limites de ação, outras en-caram as iniciativas verdes como um benefício para o negócio. O principal objetivo deste estudo é conceber um modelo de decisão que apoie as empresas na utilização sustentável das tecnologias de informação. Adicionalmente pretende-se testar a apli-cabilidade do modelo, verificando a implementação dos parâmetros de green IT nas empresas. Para tal, foram feitas comparações par a par entre os critérios correspondentes ao comporta-mento humano e à redução da energia consumida pelas infraestruturas, sendo obtidos pesos para cada parâmetro. Estes pesos foram considerados no contexto organizacional, ficando a conhecer-se o grau de implementação das iniciativas sustentáveis nas empresas estudadas. A aplicabilidade do modelo ficou provada, apesar de ser necessário um maior número de da-dos para permitir o seu emprego em contexto real. Os testes aplicados aos casos de estudo permitiram concluir que a empresa com uma utilização mais sustentável das tecnologias é a empresa de prestação de serviços.
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Okonji, Stephen Chiedu. "Multi criteria risk analysis of a subsea BOP system." Thesis, Cranfield University, 2015. http://dspace.lib.cranfield.ac.uk/handle/1826/11869.

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The Subsea blowout preventer (BOP) which is latched to a subsea wellhead is one of several barriers in the well to prevent kicks and blowouts and it is the most important and critical equipment, as it becomes the last line of protection against blowout. The BOP system used in Subsea drilling operations is considered a Safety – Critical System, with a high severity consequence following its failure. Following past offshore blowout incidents such as the most recent Macondo in the Gulf of Mexico, there have been investigations, research, and improvements sought for improved understanding of the BOP system and its operation. This informs the need for a systematic re-evaluation of the Subsea BOP system to understand its associated risk and reliability and identify critical areas/aspects/components. Different risk analysis techniques were surveyed and the Failure modes effect and criticality analysis (FMECA) selected to be used to drive the study in this thesis. This is due to it being a simple proven cost effective process that can add value to the understanding of the behaviours and properties of a system, component, software, function or other. The output of the FMECA can be used to inform or support other key engineering tasks such as redesigning, enhanced qualification and testing activity or maintenance for greater inherent reliability and reduced risk potential. This thesis underscores the application of the FMECA technique to critique associated risk of the Subsea BOP system. System Functional diagrams was developed with boundaries defined, a FMECA were carried out and an initial select list of critical component failure modes identified. The limitations surrounding the confidence of the FMECA failure modes ranking outcome based on Risk priority number (RPN) is presented and potential variations in risk interpretation are discussed. The main contribution in this thesis is an innovative framework utilising Multicriteria decision making (MCDA) analysis techniques with consideration of fuzzy interval data is applied to the Subsea BOP system critical failure modes from the FMECA analysis. It utilised nine criticality assessment criteria deduced from expert consultation to obtain a more reliable ranking of failure modes. The MCDA techniques applied includes the technique for order of Preference for similarity to the Ideal Solution (TOPSIS), Fuzzy TOPSIS, TOPSIS with interval data, and Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE). The outcome of the Multi-criteria analysis of the BOP system clearly shows failures of the Wellhead connector, LMRP hydraulic connector and Control system related failure as the Top 3 most critical failure with respect to a well control. The critical failure mode and components outcome from the analysis in this thesis is validated using failure data from industry database and a sensitivity analysis carried out. The importance of maintenance, testing and redundancy to the BOP system criticality was established by the sensitivity analysis. The potential for MCDA to be used for more specific analysis of criteria for a technology was demonstrated. Improper maintenance, inspection, testing (functional and pressure) are critical to the BOP system performance and sustenance of a high reliability level. Material selection and performance of components (seals, flanges, packers, bolts, mechanical body housings) relative to use environment and operational conditions is fundamental to avoiding failure mechanisms occurrence. Also worthy of notice is the contribution of personnel and organisations (by way of procedures to robustness and verification structure to ensure standard expected practices/rules are followed) to failures as seen in the root cause discussion. OEMs, operators and drilling contractors to periodically review operation scenarios relative to BOP system product design through the use of a Failure reporting analysis and corrective action system. This can improve design of monitoring systems, informs requirement for re-qualification of technology and/or next generation designs. Operations personnel are to correctly log in failures in these systems, and responsible Authority to ensure root cause analysis is done to uncover underlying issue initiating and driving failures.
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Dante, Elena <1995&gt. "Application of Fuzzy AHP and TOPSIS methods for a Foreign Direct Investment in the aluminium industry sector." Master's Degree Thesis, Università Ca' Foscari Venezia, 2019. http://hdl.handle.net/10579/15842.

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Multi-Criteria Decision Making (MCDM) is one of the most well-known branch of decision making, representing a starting point for solving important practical issues. In the present thesis, two methods are applied: Fuzzy AHP and TOPSIS . In order to deal with this problem, the objective of the thesis is to validate or not a future possible investment proposed by a Paduan (IT) aluminium enterprise. It would like to implement a Foreign Direct Investment (FDI) in Morocco in a local firm belonging to the same industry sector. The goal of the thesis is the identification of the best country in the Mediterranean zone where apply the FDI for a medium-large aluminium enterprise of Italian North-East. The final result will not validate the investment proposed by the Paduan firm and reward Morocco as not the best area for this type of investment. Fuzzy AHP method identifies the factors (cost, labour characteristics, political and economic factors…) necessary to consider for this type of investment, while TOPSIS method, through the previous result, creates the final rank of countries from the best one where apply an FDI for an aluminium company to the worst one.
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Books on the topic "Fuzzy TOPSIS"

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Mordeson, John N., and Sunil Mathew. Advanced Topics in Fuzzy Graph Theory. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04215-8.

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IGOShIN, Vladimir. Logic with elements of mathematical logic. ru: INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1856361.

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In the textbook, traditional logic is presented from the point of view of mathematical logic. Mathematization begins with the study of the topic "Concept", continues with the topic "Judgment" and reaches its greatest effectiveness in the study of deductive reasoning. Thus, the most effective part of traditional logic is subjected to mathematization. The issues of the relationship between logic and intuition in thought processes, the role of language in them, as well as plausible conclusions and elements of the theory of fuzzy sets and fuzzy logic are considered. Meets the requirements of the federal state educational standards of higher education of the latest generation. It is addressed primarily to students of mathematical fields of study and specialties of universities, especially future teachers of mathematics and computer science, studying both at the bachelor's and master's level at pedagogical and classical universities. It will also be useful for students of humanities and university specialties — lawyers, philosophers, political scientists, sociologists, economists, historians, philologists, linguists who study traditional logic and want to learn how mathematical methods penetrate into humanitarian fields of knowledge, including the direction of "Applied Informatics".
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Alaoui, Mohamed El. Fuzzy Topsis. Taylor & Francis Group, 2021.

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Alaoui, Mohamed El. Fuzzy TOPSIS: Logic, Approaches, and Case Studies. Taylor & Francis Group, 2021.

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Fuzzy TOPSIS: Logic, Approaches, and Case Studies. Taylor & Francis Group, 2021.

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Alaoui, Mohamed El. Fuzzy TOPSIS: Logic, Approaches, and Case Studies. Taylor & Francis Group, 2021.

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Darby, Conley. Fuzzy Bunch: A Get Fuzzy Collection. Andrews McMeel Publishing, 2013.

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Darby, Conley. Fuzzy Bunch: A Get Fuzzy Collection. Andrews McMeel Publishing, 2013.

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Darby, Conley. Fuzzy Bunch: A Get Fuzzy Collection. Andrews McMeel Publishing, 2013.

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Darby, Conley. Fuzzy Bunch: A Get Fuzzy Collection. Andrews McMeel Publishing, 2013.

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Book chapters on the topic "Fuzzy TOPSIS"

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El Alaoui, Mohamed. "Fuzzy TOPSIS." In Fuzzy TOPSIS, 95–133. First edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9781003168416-6-6.

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Gomes, Maria Isabel, and Nelson Chibeles Martins. "TOPSIS and Fuzzy TOPSIS." In Mathematical Models for Decision Making with Multiple Perspectives, 117–44. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003015154-6.

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El Alaoui, Mohamed. "Intuitionistic Fuzzy TOPSIS." In Fuzzy TOPSIS, 135–74. First edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9781003168416-7-7.

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El Alaoui, Mohamed. "Other Fuzzy TOPSIS Approaches." In Fuzzy TOPSIS, 175–97. First edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9781003168416-8-8.

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El Alaoui, Mohamed. "TOPSIS Methodology and Limits." In Fuzzy TOPSIS, 65–94. First edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9781003168416-5-5.

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El Alaoui, Mohamed. "Fuzzy Logic." In Fuzzy TOPSIS, 31–39. First edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9781003168416-3-3.

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El Alaoui, Mohamed. "Uncertainty." In Fuzzy TOPSIS, 1–13. First edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9781003168416-1-1.

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El Alaoui, Mohamed. "Nonclassical Logics." In Fuzzy TOPSIS, 15–29. First edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9781003168416-2-2.

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El 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.

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Rodríguez, Antonio. "An Integrated TOPSIS and FAHP." In Fuzzy Analytic Hierarchy Process, 139–60. Boca Raton : CRC Press, 2017.: Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315369884-6.

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Conference papers on the topic "Fuzzy TOPSIS"

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Ahmad, Sharifah Aniza Sayed, and Daud Mohamad. "A comparative analysis between fuzzy topsis and simplified fuzzy topsis." In PROCEEDINGS OF THE 24TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES: Mathematical Sciences Exploration for the Universal Preservation. Author(s), 2017. http://dx.doi.org/10.1063/1.4995904.

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Madi, Elissa Nadia, Jonathan M. Garibaldi, and Christian Wagner. "An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS." In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2016. http://dx.doi.org/10.1109/fuzz-ieee.2016.7737950.

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Elhassouny, Azeddine, and Florentin Smarandache. "Neutrosophic-simplified-TOPSIS Multi-Criteria Decision-Making using combined Simplified-TOPSIS method and Neutrosophics." In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2016. http://dx.doi.org/10.1109/fuzz-ieee.2016.7738003.

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Luukka, Pasi, and Mikael Collan. "Bonferroni mean based similarity based TOPSIS." In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2016. http://dx.doi.org/10.1109/fuzz-ieee.2016.7737756.

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Luukka, Pasi. "N—ary norm operators and TOPSIS." In 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2020. http://dx.doi.org/10.1109/fuzz48607.2020.9177580.

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Agarwal, Manish, Madasu Hanmandlu, and Kanad K. Biswas. "Choquet integral vs. TOPSIS: An intuitionistic fuzzy approach." In 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2013. http://dx.doi.org/10.1109/fuzz-ieee.2013.6622313.

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Sevkli, Mehmet, Selim Zaim, Ali Turkyilmaz, and Metin Satir. "An application of fuzzy Topsis method for supplier selection." In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584006.

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Khalif, Ku Muhammad Naim Ku, Alexander Gegov, and Ahmad Syafadhli Abu Bakar. "Z-TOPSIS approach for performance assessment using fuzzy similarity." In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2017. http://dx.doi.org/10.1109/fuzz-ieee.2017.8015458.

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"Fuzzy Similarity based Fuzzy TOPSIS with Multi-distances." In International Conference on Fuzzy Computation Theory and Applications. SCITEPRESS - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004552601930200.

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Buyukozkan, Gulcin, and Sezin Guleryuz. "An application of intuitionistic fuzzy TOPSIS on mobile phone selection." In 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2015. http://dx.doi.org/10.1109/fuzz-ieee.2015.7337915.

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Reports on the topic "Fuzzy TOPSIS"

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Paule, Bernard, Flourentzos Flourentzou, Tristan de KERCHOVE d’EXAERDE, Julien BOUTILLIER, and Nicolo Ferrari. PRELUDE Roadmap for Building Renovation: set of rules for renovation actions to optimize building energy performance. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau541614638.

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In the context of climate change and the environmental and energy constraints we face, it is essential to develop methods to encourage the implementation of efficient solutions for building renovation. One of the objectives of the European PRELUDE project [1] is to develop a "Building Renovation Roadmap"(BRR) aimed at facilitating decision-making to foster the most efficient refurbishment actions, the implementation of innovative solutions and the promotion of renewable energy sources in the renovation process of existing buildings. In this context, Estia is working on the development of inference rules that will make it possible. On the basis of a diagnosis such as the Energy Performance Certificate, it will help establishing a list of priority actions. The dynamics that drive this project permit to decrease the subjectivity of a human decisions making scheme. While simulation generates digital technical data, interpretation requires the translation of this data into natural language. The purpose is to automate the translation of the results to provide advice and facilitate decision-making. In medicine, the diagnostic phase is a process by which a disease is identified by its symptoms. Similarly, the idea of the process is to target the faulty elements potentially responsible for poor performance and to propose remedial solutions. The system is based on the development of fuzzy logic rules [2],[3]. This choice was made to be able to manipulate notions of membership with truth levels between 0 and 1, and to deliver messages in a linguistic form, understandable by non-specialist users. For example, if performance is low and parameter x is unfavourable, the algorithm can gives an incentive to improve the parameter such as: "you COULD, SHOULD or MUST change parameter x". Regarding energy performance analysis, the following domains are addressed: heating, domestic hot water, cooling, lighting. Regarding the parameters, the analysis covers the following topics: Characteristics of the building envelope. and of the technical installations (heat production-distribution, ventilation system, electric lighting, etc.). This paper describes the methodology used, lists the fields studied and outlines the expected outcomes of the project.
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