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Journal articles on the topic 'Fuzzy TOPSIS'
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1
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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Chen, Yuan, Bing Li, and Xiao Jun Yang. "An Integrated Fuzzy Multi-Attribute Decision-Making Methodology for Evaluation of Mechanical Product." Key Engineering Materials 450 (November 2010): 534–38. http://dx.doi.org/10.4028/www.scientific.net/kem.450.534.
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The concept evaluation of mechanical product is essentially a multi-attribute decision making (MADM) problem in the fuzzy environment. In order to reduce the adverse impact of preference or judgments of decision makers on the final evaluation results, this paper attempts to propose an integrated fuzzy multi-attribute decision making methodology that combines the fuzzy TOPSIS technique and the objective weighting to evaluate mechanical product. The fuzzy TOPSIS technique is applied to rank the design alternatives, and the objective weighting method is integrated into the fuzzy TOPSIS technique to determine the appropriate criteria weights. Finally, a real application to pan mechanism selection for a cooking robot is demonstrated.
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Nafis Satul Khasanah, Andi Farmadi, Dodon Turianto Nugrahadi, Muliadi, and Rudy Herteno. "SENSITIVITY TEST FUZZY TOPSIS AND FUZZY TOPSIS ROC METHODS FOR THE SELECTION OF THE SASIRANGAN BANJAR FABRIC MOTIFS." Journal of Data Science and Software Engineering 1, no. 01 (June 29, 2020): 43–52. http://dx.doi.org/10.20527/jdsse.v1i01.11.
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Decision making is one of problem that we often find in society, as well as choosing the fabric of the motif of Sasirangan Banjar that currently there are many kinds of it. So, to find out the ideal solution need the various of considerations that will make hesitation. And it will influence in time of accuracy of decision-making. Multi Atribut Decision Making (MADM) is a part of decision-making with various criteria that have a weight. The objective is to find out and ideal solution that can be optimal in implementation. The used Fuzzy TOPSIS and Fuzzy TOPSIS ROC methods an important to make an assesment with a simple system and calculation of priority weights to produces various motives. The result of two methods that have been test sensitivity are the best decision with the result 7,16% for weight Rank Order Centroid (ROC) and 0,6% for weight TOPSIS. So, Fuzzy TOPSIS ROC is better in values weight because it has a higher sensitivity than the Fuzzy TOPSIS.
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Kar, Mr UditNarayan, Miss Arunima Kar, and Miss Anyatama Kar. "EVALUATING PARETO FRONT WITH TOPSIS AND FUZZY TOPSIS FOR LITERACY RATES IN ODISHA." EPH - International Journal of Science And Engineering 1, no. 2 (June 27, 2015): 11–23. http://dx.doi.org/10.53555/eijse.v1i2.40.
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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 created a 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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Jefmański, Bartłomiej, and Adam Sagan. "Item Response Theory Models for the Fuzzy TOPSIS in the Analysis of Survey Data." Symmetry 13, no. 2 (January 29, 2021): 223. http://dx.doi.org/10.3390/sym13020223.
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The fuzzy TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) is an attractive tool for measuring complex phenomena based on uncertain data. The original version of the method assumes that the object assessments in terms of the adopted criteria are expressed as triangular fuzzy numbers. One of the crucial stages of the fuzzy TOPSIS is selecting the fuzzy conversion scale, which is used to evaluate objects in terms of the adopted criteria. The choice of a fuzzy conversion scale may influence the results of the fuzzy TOPSIS. There is no uniform approach in constructing and selecting the fuzzy conversion scale for the fuzzy TOPSIS. The choice is subjective and made by researchers. Therefore, the aim of the article is to present a new, objective approach to the construction of fuzzy conversion scales based on Item Response Theory (IRT) models. The following models were used in the construction of fuzzy conversion scales: Polychoric Correlation Model (PM), Polytomous Rasch Model (PRM), Rating Scale Model (RSM), Partial Credit Model (PCM), Generalized Partial Credit Model (GPCM), Graded Response Model (GRM), Nominal Response Model (NRM). The usefulness of the proposed approach is presented on the example of the analysis of a survey’s results on measuring the quality of professional life of inhabitants of selected communes in Poland. The obtained results indicate that the choice of the fuzzy conversion scale has a large impact on the closeness coefficient values. A large difference was also observed in the spreads of triangular fuzzy numbers between scales based on IRT models and those used in the literature on the subject. The use of the fuzzy TOPSIS with fuzzy conversion scales built based on PRM, RSM, PCM, GPCM, and GRM models gives results with a greater range of variability than in the case of fuzzy conversion scales used in empirical research.
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Rahmalia, Dinita, Awawin Mustana Rohmah, and Nuril Lutvi Azizah. "Analytic Hierarchy Process (AHP) dan Fuzzy TOPSIS pada Pemilihan Himpunan Pairing Terpilih dari Jadwal Penerbangan." JATI UNIK : Jurnal Ilmiah Teknik dan Manajemen Industri 4, no. 1 (October 30, 2020): 1. http://dx.doi.org/10.30737/jatiunik.v4i1.922.
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In the flight industry, there are two highest costs such as fuel cost and crew cost. The crew cost is affected by pairings selected from flight schedule. This research will explain about selecting the set of selected pairings using Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order Performance by Similarity to Ideal Solution (Fuzzy TOPSIS). Before using either Fuzzy AHP or Fuzzy TOPSIS, it will be formed collection of the set of selected pairings using greedy algorithm. After collection of the set of selected pairings is formed, then we determine goal and criteria. The goal is selecting the set of selected pairings from some alternatives. For each the set of selected pairings, there are some criterions such as the number of deadhead, the number of pairing A2, the number of pairing A3, the number of pairing A4, the number of pairing A5, and the number of pairing A6. Based on simulation results, both AHP and Fuzzy TOPSIS can select and give the rank of priority in entire the set of selected pairings. Pada industri maskapai penerbangan, terdapat dua biaya yang sangat besar yaitu biaya bahan bakar dan biaya kru. Biaya kru dipengaruhi oleh pairing yang terpilih dari jadwal penerbangan. Pada penelitian ini akan dilakukan pemilihan himpunan pairing terpilih menggunakan metode Analytic Hierarchy Process (AHP) dan Fuzzy Technique for Order Performance by Similarity to Ideal Solution (Fuzzy TOPSIS). Sebelum menggunakan AHP atau Fuzzy TOPSIS, akan dibentuk kumpulan dari himpunan pairing terpilih menggunakan greedy algorithm. Setelah kumpulan himpunan pairing terpilih terbentuk, maka dibentuk goal dan kriteria. Goal adalah memilih himpunan pairing terpilih dari beberapa alternative. Pada setiap himpunan pairing yang terpilih, terdapat beberapa kriteria seperti jumlah deadhead, jumlah pairing A2, jumlah pairing A3, jumlah pairing A4, jumlah pairing A5, dan jumlah pairing A6. Berdasarkan hasil perhitungan, metode AHP dan Fuzzy TOPSIS dapat memilih dan memberi peringkat prioritas pada pemilihan himpunan pairing terpilih.
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Park, Daeryong, Huan-Jung Fan, Jun-Jie Zhu, Taesoon Kim, Myoung-Jin Um, Siyeon Kim, Seol Jeon, and Kichul Jung. "Prioritization in Strategic Environmental Assessment Using Fuzzy TOPSIS Method with Random Generation for Absent Information in South Korea." Sustainability 13, no. 3 (January 30, 2021): 1458. http://dx.doi.org/10.3390/su13031458.
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This study evaluated a fuzzy technique for order performance by similarity to ideal solution (TOPSIS) as a multicriteria decision making system that compensates for missing information with undefined weight factor criteria. The suggested Fuzzy TOPSIS was applied to ten potential dam sites in three river basins (the Han River, the Geum River, and the Nakdong River basins) in South Korea. To assess potential dam sites, the strategic environment assessment (SEA) monitored four categories: national preservation, endangered species, water quality, and toxic environment. To consider missing information, this study applied the Monte Carlo Simulation method with uniform and normal distributions. The results show that effects of missing information generation with one fuzzy set in GB1 site of the Geum River basin are not great in fuzzy positive-ideal solution (FPIS) and fuzzy negative-ideal solution (FNIS) estimations. However, the combination of two fuzzy sets considering missing information in Gohyun stream (NG) and Hoenggye stream (NH) sites of the Nakdong River basin has a great effect on estimating FPIS, FNIS, and priority ranking in Fuzzy TOPSIS applications. The sites with the highest priority ranking in the Han River, Geum River, and Nakdong River basins based on Fuzzy TOPSIS are the Dal stream 1 (HD1), Bocheong stream 2 (GB2) and NG sites. Among the sites in all river basins, the GB2 site had the highest priority ranking. Consequently, the results coincided with findings of previous studies based on multicriteria decision making with missing information and show the applicability of Fuzzy TOPSIS when evaluating priority rankings in cases with missing information.
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He, Yuan Yuan, and Zai Wu Gong. "TOPSIS Method for Multiple Attribute Decision Making Problem in Intuitionistic Fuzzy Setting." Applied Mechanics and Materials 427-429 (September 2013): 1888–91. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.1888.
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This paper is concerned with a TOPSIS method for fuzzy multiple attribute decision making, in which the information about attribute weights is completely known and the attribute values take form of intuitionistic fuzzy numbers. A class of distance for describing the deviation degrees between intuitionistic fuzzy sets is used to measure difference between two alternatives. A model of TOPSIS is designed with the introduction of the particular closeness coefficient composed of similarity degrees. Then, we apply the TOPSIS method to aggregate the fuzzy information corresponding to each alternative, and rank the alternatives according to their closeness coefficients. Finally, a numerical example is given to show the feasibility and effectiveness of the method.
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Lima Junior, Francisco Rodrigues, and Luiz Cesar Ribeiro Carpinetti. "Uma comparação entre os métodos TOPSIS e Fuzzy-TOPSIS no apoio à tomada de decisão multicritério para seleção de fornecedores." Gestão & Produção 22, no. 1 (March 2015): 17–34. http://dx.doi.org/10.1590/0104-530x1190.
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A seleção de fornecedores é considerada a atividade mais crítica da função de compras e impacta diretamente a qualidade dos produtos manufaturados e o desempenho do comprador. Na literatura acadêmica, dezenas de métodos de tomada de decisão multicritério vêm sendo explorados para apoiar a seleção de fornecedores. Dentre esses, o TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) e o Fuzzy-TOPSIS (uma adaptação do primeiro) se destacam por sua simplicidade de uso e pela capacidade de avaliar um número ilimitado de alternativas e critérios simultaneamente. Embora muitos autores sugiram a adoção do TOPSIS e do Fuzzy-TOPSIS para suportar a seleção de fornecedores, na literatura não são discutidas as reais vantagens de uso e as limitações destes métodos quando aplicados neste domínio de problema. Diante de tal lacuna, este estudo compara o TOPSIS e o Fuzzy-TOPSIS, em relação à complexidade computacional, à estrutura dos algoritmos e aos resultados fornecidos quando aplicados em um mesmo caso real de seleção de fornecedores. Os métodos foram implementados usando MATLAB(r) e aplicados na seleção de fornecedores de uma empresa de cabos de transmissão. Os resultados mostram que o TOPSIS requer menor esforço para coleta de dados e processamento computacional. Em contrapartida, o Fuzzy-TOPSIS não sofre inversões no ranking e se mostra adequado para lidar com informações qualitativas e imprecisas. Os resultados deste estudo podem orientar pesquisadores e profissionais na escolha do método mais adequado para lidar com o problema de seleção de fornecedores em questão.
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Ambrin, Rabia, Muhammad Ibrar, Manuel De La Sen, Ihsan Rabbi, and Asghar Khan. "Extended TOPSIS Method for Supplier Selection under Picture Hesitant Fuzzy Environment Using Linguistic Variables." Journal of Mathematics 2021 (April 20, 2021): 1–28. http://dx.doi.org/10.1155/2021/6652586.
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The main purpose of this planned manuscript is to establish an algorithm for the solution of multiattribute decision-making (MADM) issues, where the experts utilizing linguistic variables provide the information about attributes in the form of picture hesitant fuzzy numbers. So, for the solution of these kinds of issues, we develop the TOPSIS algorithm under picture hesitant fuzzy environment using linguistic variables, which plays a vital role in practical applications, notably MADM issues, where the decision information is arranged by the decision-makers (DMs) in the form of picture hesitant fuzzy numbers. Finally, a sample example is given as an application and appropriateness of the planned method. At the end, we conduct comparison analysis of the planned method with picture fuzzy TOPSIS method and intuitionistic fuzzy TOPSIS method.
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Jun, H. U., W. U. Junmin, and W. U. Jie. "TOPSIS Hybrid Multiattribute Group Decision-Making Based on Interval Pythagorean Fuzzy Numbers." Mathematical Problems in Engineering 2021 (December 3, 2021): 1–8. http://dx.doi.org/10.1155/2021/5735272.
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Aiming at the mixed multiattribute group decision-making problem of interval Pythagorean fuzzy numbers, a weighted average (WA) operator model based on interval Pythagorean fuzzy sets is constructed. Furthermore, a decision-making method based on the technique for order preference by similarity to ideal solution (TOPSIS) method with interval Pythagorean fuzzy numbers is proposed. First, based on the completely unknown weights of decision-makers and attributes, interval Pythagorean fuzzy numbers are applied to TOPSIS group decision-making. Second, the interval Pythagorean fuzzy number WA operator is used to synthesize the evaluation matrices of multiple decision-makers into a comprehensive evaluation matrix, and the relative closeness of each scheme is calculated based on the TOPSIS decision-making method. Finally, an example is given to illustrate the rationality and effectiveness of the proposed method.
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Septiyana, Diah, and Galang P. N. Hakim. "PENERAPAN FUZZY TOPSIS UNTUK PEMILIHAN PEMASOK PADA DEPARTEMEN SUPPLY CHAIN DI PERUSAHAAN PENGOLAHAN AIR KABUPATEN TANGERANG." Journal Industrial Manufacturing 3, no. 2 (July 15, 2018): 1. http://dx.doi.org/10.31000/jim.v3i2.827.
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Dalam proses pengadaan di departemen Supply Chain metode pemilihan pemasok sangatlah problematic karena ketidakpastian pemilihan pemasok yang diakibatkan oleh adanya ego dan perasaan manusia sebagai salah satu penentu keputusan. Oleh karena itu, dengan adanya penggunaan metode FUZZY TOPSIS untuk memecahkan masalah pemilihan pemasok ini. Metode FUZZY TOPSIS menentukan pemasok yang memiliki kinerja terbaik dengan menggunakan kriteria yang diberikan oleh pengguna. Dengan menggunakan metode ini keputusan pemilihan pemasok dapat melakukan secara otomatis menggunakan sistem IT pada perusahaan masing-masing, sehingga dapat meminimalkan masalah pengguna dari memilih pemasok terbaik. Contoh dari ini adalah proyek oleh Perusahaan Pengolahan Air di Kabupaten Tangerang untuk menemukan pemasok terbaik dalam sistem distribusi air. Untuk pemasok yang DEI, HP, dan KSP dan diberikan criteria pengguna seperti “Commercial by Costumer”, “Technical Proposal”, “Work Plan & methodology”, dan “Staff Competence”. Dengan menggunakan criteria pengguna untuk membuat matriks keputusan sebagai masukan untuk FUZZY TOPSIS. Hasilnya adalah pemasok KSP menunjukkan performa terbaik dengan nilai 0.50078 lebih baik dari pemasok lainnya.Kata Kunci : fuzzy topsis, supply chain, ERP, pemasok.
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Kaur, Ramandeep, and Sumit Mittal. "Enhanced Handoff Decision Making for Application-Aware Environment by Using Blended Approach." International Journal of Intelligent Engineering and Systems 14, no. 1 (February 28, 2021): 433–43. http://dx.doi.org/10.22266/ijies2021.0228.40.
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Seamless integration of the new and existing networks is required to create next generation wireless networks capable of providing wide range of services coupled with uninterrupted connectivity and high speeds offering unprecedented quality of service to users. Smooth and proficient handoff techniques are important to achieve optimal network performance in heterogeneous wireless environments. This paper proposes Multiple Criteria Decision Making (MCDM) techniques of both non-fuzzy (Technique for Order of Performance by Similarity to Ideal Solution (TOPSIS)) and fuzzy (Fuzzy TOPSIS (FTOPSIS)) type for network ranking. The proposed algorithm uses priority ranking to assign weights to six parameters by using Fuzzy Analytic Hierarchy Process (FAHP). Further, TOPSIS and FTOPSIS techniques are compared for various traffic classes and used for network selection in the prevalent network conditions. The results show that contingent on the traffic classes, the FTOPSIS selects the ideal network with diminished ping-pong rate and call blocking probability as compared to TOPSIS while accounting for the uncertain environment.
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Cao, Junli, and Fangfang Xu. "Entropy-Based Fuzzy TOPSIS Method for Investment Decision Optimization of Large-Scale Projects." Computational Intelligence and Neuroscience 2022 (July 18, 2022): 1–11. http://dx.doi.org/10.1155/2022/4381293.
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Investment of large-scale projects must consider various factors, such as economic conditions and investment environment when making decisions. In large-scale project investment problems, almost 90% of them are completed in a multiobjective context. To this end, the authors of this paper have proposed an entropy-based fuzzy TOPSIS synthesis method to assist in the decision-making optimization of large-scale project investment. Firstly, in accordance with the background of the development of multiattribute decision-making method (MADM), closely related to large-scale project investment, the related research works were studied, and the relevant methods are sorted out. Then, the improved vague-entropy-weight based fuzzy TOPSIS (VEWF-TOPSIS) method, entropy and interval language intuitionistic fuzzy sets based TOPSIS (EILIF-TOPSIS) method, and information entropy attribute importance based intuitionistic fuzzy TOPSIS (IEAI-IF-TOPSIS) method were introduced, and a synthesis MADM method that comprehensively combines the above three methods was proposed. Finally, a numerical case was constructed to properly show the effectiveness of the method proposed in the present work, and the conclusions were put forward for providing ideas and methods for large-scale project investment decision-making. It is of great significance that the proposed framework would make large-scale project investment decisions more reasonable and practical, which enriches the research methods of MADM problems to a certain extent and can provide reference for the actual large-scale project investment decision-making problems.
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Chopra, Neeraj, Rajiv Sindwani, and Manisha Goel. "A Hybrid Approach Based on Fuzzy TOPSIS-AHP for Ranking and Classifying MOOC Key Acceptance Factors." International Journal of Web-Based Learning and Teaching Technologies 16, no. 5 (September 2021): 1–20. http://dx.doi.org/10.4018/ijwltt.20210901.oa1.
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This investigation is done during COVID-19 to identify, rank, and classify MOOC (massive open online course) key acceptance factors (KAFs) from an Indian perspective. A systematic literature review identifies 11 KAFs of MOOC. One more novel factor named ‘contingent instructor' is proposed by the authors considering pandemic and new normal post-COVID-19. The paper implements two popular fuzzy MCDM (multiple-criteria decision-making) techniques, namely fuzzy TOPSIS and fuzzy AHP, on 12 KAFs. The fuzzy TOPSIS approach is used to rank factors. Affordability, performance expectancy and digital didactics are found as the top three KAFs. Fuzzy AHP classified KAFs into three groups, namely high, moderate, and low influential. Examination of the literature indicates that this study is among the first attempt to prioritize and classify MOOC KAFs using fuzzy TOPSIS and fuzzy AHP approach. The results offer managerial guidance to stakeholders for effective management of MOOC, resulting in higher acceptance rate. Likewise, this investigation will upgrade the comprehension of MOOC KAFs among academicians.
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Luukka, Pasi. "Fuzzy Similarity in Multicriteria Decision-Making Problem Applied to Supplier Evaluation and Selection in Supply Chain Management." Advances in Artificial Intelligence 2011 (December 22, 2011): 1–9. http://dx.doi.org/10.1155/2011/353509.
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It is proposed to use fuzzy similarity in fuzzy decision-making approach to deal with the supplier selection problem in supply chain system. According to the concept of fuzzy TOPSIS earlier methods use closeness coefficient which is defined to determine the ranking order of all suppliers by calculating the distances to both fuzzy positive-ideal solution (FPIS) and fuzzy negative-ideal solution (FNIS) simultaneously. In this paper we propose a new method by doing the ranking using similarity. New proposed method can do ranking with less computations than original fuzzy TOPSIS. We also propose three different cases for selection of FPIS and FNIS and compare closeness coefficient criteria and fuzzy similarity criteria. Numerical example is used to demonstrate the process. Results show that the proposed model is well suited for multiple criteria decision-making for supplier selection. In this paper we also show that the evaluation of the supplier using traditional fuzzy TOPSIS depends highly on FPIS and FNIS, and one needs to select suitable fuzzy ideal solution to get reasonable evaluation.
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Nisa, Khoirun. "Aplikasi Pemilihan Vendor Menggunakan Metode Fuzzy AHP Dan TOPSIS." Jurnal Ilmiah Media Sisfo 16, no. 1 (April 30, 2022): 20. http://dx.doi.org/10.33998/mediasisfo.2022.16.1.1159.
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Pemilihan vendor yang tepat merupakan hal yang sangat penting dalam menjalankan proses bisnis. Perusahaan perlu mempertimbangkan faktor-faktor penting dalam memilih vendor yang tepat. Penawaran harga yang rendah sudah tidak efisien lagi dalam pemilihan vendor saat ini. Pada penelitian ini kombinasi Fuzzy AHP dan TOPSIS akan digunakan dalam pemilihan vendor pada salah satu perusahaan sales dan distribusi di Jakarta. Dalam penelitian ini TOPSIS digunakan untuk melakukan perankingan alternatif berdasarkan kriteria yang ditetapkan yang telah dihitung nilai bobotnya menggunakan metode Fuzzy AHP. Bobot preferensi masing-masing kriteria yang dihasilkan oleh dan Fuzzy AHP adalah sebesar 0.453718 untuk harga, 0.01616 untuk kriteria jumlah teknisi professional, 0.144174 untuk kriteria metodologi pelaksanan pekerjaan dan 0.385948 untuk kriteria pengalaman perusahaan. Perangkingan yang dihasilkan TOPSIS adalah PT. Nusa Network Prakarsa pada urutan pertama, PT. Mitra Integrasi Informatika pada urutan kedua dan PT. Iproteksi Telematika pada urutan ketiga. Setelah hasil perankingan diketahui dilakukan evaluasi terhadap hubungan masing-masing kriteria dengan hasil akhir TOPSIS dengan menghitung nilai korelasi Pearson. Setelah itu hasil akhir TOPSIS dan hasil ranking dihitung korelasinya untuk mengetahui seberapa kuat hubungan semua atribut atau kriteria terhadap hasil perankingan.
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Akram, Muhammad, Maheen Sultan, and Ahmad N. Al-Kenani. "Group Decision Analysis Based on Complex m-Polar Fuzzy N-Soft Environment." Mathematical Problems in Engineering 2022 (April 26, 2022): 1–24. http://dx.doi.org/10.1155/2022/4917408.
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This research article presents a novel multicriteria group decision-making (MCGDM) technique, namely, complex m-polar fuzzy N-soft TOPSIS (CmPFNS-TOPSIS), that incorporates the remarkable features of manipulating the complex two-dimensional data and the multipolarity of the modern era with the help of CmPFNSS and the multicriteria group decision making potential of the TOPSIS technique. This newly proposed technique shares a very general parametric structure of the CmPFMSS and enables us to make the suitable decisions in this multipolar complex two-dimensional domain. The incredible CmPFNS-TOPSIS technique works on the principle of finding the optimal solution nearest to the positive ideal solution (PSS) and farthest from the negative ideal solution (NIS) by evaluating the Euclidean distance between the alternatives and the optimal solutions. The support of complex m-polar fuzzy N-soft weighted averaging operator (CmPFNSWA), Euclidean distance, score function, and the revised closeness index is utilized for uncovering our optimal solutions. The alternatives, with respect to the revised closeness index, are arranged in the descending order and the alternative with the least closeness index is preferred. The methodology of the CmPFNS-TOPSIS technique is illustrated with the help of the flow chart. The proficiency of this technique is proved by considering a case study of selection of the suitable surgical equipment in the oncology department of Shaukat Khanum Hospital, Lahore (Pakistan). To prove its validity and credibility, a comparative analysis between CmPFNS-TOPSIS and m-polar fuzzy N-soft TOPSIS (mFNS-TOPSIS) is pictured with the help of a bar chart displaying the same end results of the CmPFNS-TOPSIS and mFNS-TOPSIS.
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Akram, Muhammad, Maheen Sultan, and Ahmad N. Al-Kenani. "Group Decision Analysis Based on Complex m-Polar Fuzzy N-Soft Environment." Mathematical Problems in Engineering 2022 (April 26, 2022): 1–24. http://dx.doi.org/10.1155/2022/4917408.
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This research article presents a novel multicriteria group decision-making (MCGDM) technique, namely, complex m-polar fuzzy N-soft TOPSIS (CmPFNS-TOPSIS), that incorporates the remarkable features of manipulating the complex two-dimensional data and the multipolarity of the modern era with the help of CmPFNSS and the multicriteria group decision making potential of the TOPSIS technique. This newly proposed technique shares a very general parametric structure of the CmPFMSS and enables us to make the suitable decisions in this multipolar complex two-dimensional domain. The incredible CmPFNS-TOPSIS technique works on the principle of finding the optimal solution nearest to the positive ideal solution (PSS) and farthest from the negative ideal solution (NIS) by evaluating the Euclidean distance between the alternatives and the optimal solutions. The support of complex m-polar fuzzy N-soft weighted averaging operator (CmPFNSWA), Euclidean distance, score function, and the revised closeness index is utilized for uncovering our optimal solutions. The alternatives, with respect to the revised closeness index, are arranged in the descending order and the alternative with the least closeness index is preferred. The methodology of the CmPFNS-TOPSIS technique is illustrated with the help of the flow chart. The proficiency of this technique is proved by considering a case study of selection of the suitable surgical equipment in the oncology department of Shaukat Khanum Hospital, Lahore (Pakistan). To prove its validity and credibility, a comparative analysis between CmPFNS-TOPSIS and m-polar fuzzy N-soft TOPSIS (mFNS-TOPSIS) is pictured with the help of a bar chart displaying the same end results of the CmPFNS-TOPSIS and mFNS-TOPSIS.
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Fahmi, Aliya, Muhammad Aslam, and Saleem Abdullah. "Analysis of migraine in mutlicellular organism based on trapezoidal neutrosophic cubic hesitant fuzzy TOPSIS method." International Journal of Biomathematics 12, no. 08 (November 2019): 1950084. http://dx.doi.org/10.1142/s1793524519500840.
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In this paper, we define a new idea of trapezoidal neutrosophic cubic hesitant fuzzy number based on migraine diseases. We define and the migraine diseases on trapezoidal neutrosophic cubic hesitant fuzzy number and operational laws of trapezoidal neutrosophic cubic hesitant fuzzy number and hamming distance of TrNCHFNs. The new concept of trapezoidal neutrosophic cubic hesitant fuzzy TOPSIS method is introduced. Furthermore, we extend MCDM method based on the trapezoidal neutrosophic cubic hesitant fuzzy TOPSIS method. Finally, an illustrative example is given to verify and demonstrate the practicality and effectiveness of the proposed method.
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Ece, Oguzhan, and Ahmet Serhat Uludag. "Applicability of Fuzzy TOPSIS Method in Optimal Portfolio Selection and an Application in BIST." International Journal of Economics and Finance 9, no. 10 (September 10, 2017): 107. http://dx.doi.org/10.5539/ijef.v9n10p107.
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General structure of saving-investment cycle and the effectiveness of this structure are included in the most significant issues of the financial system. One of the points of intervention in providing an effective saving-investment cycle is possible through channeling the savings toward optimal investment fields. This study aims at detecting the existence of alternative methods in determining optimal selection combination in the risk and revenue perspective of individual and corporate investors who would like to evaluate their savings in capital markets. For this purpose, the applicability of Fuzzy TOPSIS method, one of the multi-criteria decision making techniques in optimal portfolio selection was researched. The applicability of the stock investment alternatives ranked according to Fuzzy TOPSIS method was examined by comparing them to the optimal selection results determined according to Markowitz, one of the modern portfolio management techniques. In the study where performance indexes were used as assessment criteria the results of both methods were discussed in terms of risk at a certain revenue level and revenue at a certain risk level through Johnson and Sharp Indexes. The results obtained determined that the Fuzzy TOPSIS portfolio alternatives created using Fuzzy TOPSIS method revealed quite positive results in terms of performance, revenue and risk and pointed at applicability of Fuzzy TOPSIS method in optimal portfolio selection as well.
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Nădăban, Sorin, Simona Dzitac, and Ioan Dzitac. "Fuzzy TOPSIS: A General View." Procedia Computer Science 91 (2016): 823–31. http://dx.doi.org/10.1016/j.procs.2016.07.088.
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Kim, Yeong-Kyu, Eun-Sung Chung, and Kil-Seong Lee. "Fuzzy TOPSIS Approach to Flood Vulnerability Assessment in Korea." Journal of Korea Water Resources Association 45, no. 9 (September 30, 2012): 901–13. http://dx.doi.org/10.3741/jkwra.2012.45.9.901.
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Ilieva, Galina. "TOPSIS Modification with Interval Type-2 Fuzzy Numbers." Cybernetics and Information Technologies 16, no. 2 (June 1, 2016): 60–68. http://dx.doi.org/10.1515/cait-2016-0020.
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Abstract This paper proposes a new TOPSIS with interval type-2 fuzzy numbers. The extension applies graded mean integration to compare normal fuzzy trapezoidal sets. It is demonstrated by a numerical example for ranking business intelligence software that the TOPSIS modification can operate with qualitative and quantitative criteria, reduces evaluation uncertainty and provides a feasible solution.
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Kutlu Gündoğdu, Fatma, and Cengiz Kahraman. "Spherical fuzzy sets and spherical fuzzy TOPSIS method." Journal of Intelligent & Fuzzy Systems 36, no. 1 (February 16, 2019): 337–52. http://dx.doi.org/10.3233/jifs-181401.
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Matawale, Chhabi Ram, Saurav Datta, and S. S. Mahapatra. "Supplier selection in agile supply chain." Benchmarking: An International Journal 23, no. 7 (October 3, 2016): 2027–60. http://dx.doi.org/10.1108/bij-07-2015-0067.
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Purpose The recent global market trend is seemed enforcing existing manufacturing organizations (as well as service sectors) to improve existing supply chain systems or to take up/adapt advanced manufacturing strategies for being competitive. The concept of the agile supply chain (ASC) has become increasingly important as a means of achieving a competitive edge in highly turbulent business environments. An ASC is a dynamic alliance of member enterprises, the formation of which is likely to introduce velocity, responsiveness, and flexibility into the manufacturing system. In ASC management, supplier/partner selection is a key strategic concern. Apart from traditional supplier/partner selection criteria; different agility-related criteria/attributes need to be taken under consideration while selecting an appropriate supplier in an ASC. The paper aims to discuss these issues. Design/methodology/approach Therefore, evaluation and selection of potential supplier in an ASC have become an important multi-criteria decision making problem. Most of the evaluation criteria being subjective in nature; traditional decision-making approaches (mostly dealing with objective data) fail to solve this problem. However, fuzzy set theory appears an important mean to tackle with vague and imprecise data given by the experts. In this work, application potential of the fuzzy multi-level multi-criteria decision making (FMLMCDM) approach proposed by Chu and Velásquez (2009) and Chu and Varma (2012) has been examined and compared to that of Fuzzy-techniques for order preference by similarity to ideal solution (TOPSIS) and Fuzzy-MOORA in the context of supplier selection in ASC. Findings It has been observed that similar ranking order appears in FMLMCDM as well as Fuzzy-TOPSIS. In Fuzzy-MOORA, the best alternative appears same as in case of FMLMCDM as well as Fuzzy-TOPSIS; but for other alternatives ranking order differs. A comparative analysis has also been made in view of working principles of FMLMCDM, Fuzzy-TOPSIS as well as Fuzzy-MOORA. Originality/value Application feasibility of FMLMCDM approach has been verified in comparison with Fuzzy-TOPSIS and Fuzzy-MOORA in the context of agile supplier selection.
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Zolkepli, Maslina, and Teh Noranis Mohd Aris. "Fuzzy AHP and TOPSIS in Cross Domain Collaboration Recommendation with Fuzzy Visualization Representation." International Journal of Machine Learning and Computing 9, no. 6 (December 2019): 849–54. http://dx.doi.org/10.18178/ijmlc.2019.9.6.882.
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Zolkepli, Maslina, and Teh Noranis Mohd Aris. "Fuzzy AHP and TOPSIS in Cross Domain Collaboration Recommendation with Fuzzy Visualization Representation." International Journal of Machine Learning and Computing 10, no. 6 (December 2020): 746–51. http://dx.doi.org/10.18178/ijmlc.2020.10.6.1000.
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Marpaung, Dinda Oktari Putri, and Esther Sorta Mauli Nababan. "Analisis pengambilan keputusan terhadap pemilihan portofolio saham terbaik menggunakan metode fuzzy analytical hierarchy process dan fuzzy topsis." Majalah Ilmiah Matematika dan Statistika 22, no. 2 (September 29, 2022): 266. http://dx.doi.org/10.19184/mims.v22i2.32912.
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The proses of decision-making in stock investment considers criteria based on the personal preferences of each investor. In addition, investors also need to analyze fundamental factors that include quantitative and qualitative criteria in which external or internal factors are affecting the company. This is because stocks have a high level of risk, so the selection of a portfolio must be done with the right decision. In making decisions based on many criteria can use fuzzy AHP (analytical hierarchy process) and fuzzy TOPSIS methods. The use of fuzzy logic because it can to cope the subjective assessment result of investor preferences. The fuzzy AHP method is applied to obtain the weights of each criterion which are the factors of stock fundamental analysis. The fuzzy TOPSIS method is applied to determine the ranking of alternatives. Based on the analysis and calculation, the most influential sub criteria is inflation rate and top alternative is the company with the BBNI stock code.
Keywords: Decision-making, Fuzzy AHP, Fuzzy TOPSIS MSC2020: 90B50, 91B06, 62C86
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Aktas, Ahmet, Billur Ecer, and Mehmet Kabak. "A Hybrid Hesitant Fuzzy Model for Healthcare Systems Ranking of European Countries." Systems 10, no. 6 (November 16, 2022): 219. http://dx.doi.org/10.3390/systems10060219.
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Ranking several countries on a specific area may require the consideration of various factors simultaneously. To obtain a ranking of countries, the development of analytical approaches, which can aggregate opinions of a group of people on various criteria, is essential. The main aim of this study was to propose such a ranking approach for European countries in terms of healthcare services. To this end, a hybrid group decision-making model based on Hesitant Fuzzy Linguistic Terms Set (HFLTS) and Hesitant Fuzzy Technique of Order Preference by Similarity to Ideal Solution (HF-TOPSIS) is presented in this study. Importance degree of indicators were determined by the HFLTS-based group decision-making approach, and then HF-TOPSIS was used to obtain the rank of countries. According to the results obtained by the proposed model, Austria, Sweden and Finland are the best European countries in terms of healthcare services. Moreover, two comparative analyses, one for the utilization of different hesitant fuzzy distance measures in HF-TOPSIS and one for the ranking of countries obtained by utilizing TOPSIS, return some variations in country rankings. While Austria remained the best country for all distance measures in the hesitant fuzzy environment, Luxemburg was found to be the best for the deterministic case of TOPSIS.
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Lin, Mingwei, Chao Huang, and Zeshui Xu. "TOPSIS Method Based on Correlation Coefficient and Entropy Measure for Linguistic Pythagorean Fuzzy Sets and Its Application to Multiple Attribute Decision Making." Complexity 2019 (October 30, 2019): 1–16. http://dx.doi.org/10.1155/2019/6967390.
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The linguistic Pythagorean fuzzy set (LPFS) is an important implement for modeling the uncertain and imprecise information. In this paper, a novel TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method is proposed for LPFSs based on correlation coefficient and entropy measure. To this end, the correlation coefficient is proposed for the relationship measurement between LPFSs. Afterwards, two entropy measures are developed to calculate the attribute weight information. Then, a novel linguistic Pythagorean fuzzy TOPSIS (LPF-TOPSIS) method is proposed to solve multiple attribute decision-making problems. Finally, the LPF-TOPSIS method is applied to handle a case concerning the selection of firewall productions, and then, a case concerning the security evaluation of computer systems is given to conduct the comparative analysis between the proposed LPF-TOPSIS method and previous decision-making methods for validating the superiority of the proposed LPF-TOPSIS method.
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Omidi, Katayoun, Afsaneh Afzali, Hossein Vahidi, and Sheida Mahnam. "Ranking of Suitable Areas for Establishing Industries in Kashan City Using VIKOR and TOPSIS Methods in Fuzzy Environment." Journal of Advances in Environmental Health Research 10, no. 2 (April 1, 2022): 133–48. http://dx.doi.org/10.32598/jaehr.10.2.1241.
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Background: In this research, among the Multi Criteria Decision Making (MCDM) methods, a combination of VIKOR and TOPSIS methods with fuzzy set theory was used to overcome the uncertainty in the ranking of alternatives. The purpose of this paper was to locate the industries of Kashan City and rank the appropriate alternatives using analytic hierarchical process (AHP) and the prioritization methods of fuzzy VIKOR and fuzzy TOPSIS. Methods: In this study, first, the effective criteria in GIS (Geographic Information System) were examined and standardized according to fuzzy logic. Then, by presenting expert opinion through AHP, the criteria were weighted, and in order to determine suitable places for establishing industries, according to the required minimum area, six alternatives were extracted from the weighted linear combination method. Subsequently, the alternatives were ranked using fuzzy VIKOR and fuzzy TOPSIS methods. The sensitivity analysis was performed in the fuzzy TOPSIS method by shifting the criteria weights and producing different weighting scenarios. The fuzzy VIKOR method was analyzed for different values of the υ variable. Results: Weighting of criteria by AHP showed that the distance from surface water with a weight coefficient of 0.200 was the most important one. according to the required minimum area, six alternatives were extracted from the weighted linear combination method. Conclusion: The sensitivity analysis of both methods showed that 405 hectares in the Southeast of Kashan are the best ones to establish industries.
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Seh, Adil Hussain, Masood Ahmad, Mohd Nadeem, Abhishek Kumar Pandey, Alka Agrawal, Rajeev Kumar, and Raees Ahmad Khan. "Usable-Security Assessment of Healthcare Software System Through Fuzzy ANP-TOPSIS Method." International Journal of System Dynamics Applications 10, no. 4 (October 1, 2021): 1–24. http://dx.doi.org/10.4018/ijsda.304444.
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To address this research possibility, the present empirical study undertakes the assessment of usable-security of healthcare software system. The attributes considered for the assessment are: four factors at first level; thirteen sub-factors at the second level with six Hospital Management Software Systems (HMSS) as alternatives. Fuzzy Analytic Network Process (F-ANP) has been applied for evaluating the weights of the attributes and their relationship with one other. Finally, fuzzy Technique for Order of Preference by Similarity to Ideal Solutions (F-TOPSIS) technique has been applied and alternatives ranking has been estimated. Results of the study conclude that HMSS-1 provides better usable–security. Furthermore, as analysed, F-TOPSIS produced more convincing results in assessing the usable-security of the HMSS. This research analysis also corroborates that when compared with the Classical ANP TOPSIS, the Fuzzy-ANP TOPSIS is the ideal methodology for producing accurate results.
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Liu, Mingyang, Wenge Qin, and Shuang Yang. "Analysis of the Advantages and Disadvantages of Four Comprehensive Evaluation Methods." Frontiers in Business, Economics and Management 9, no. 3 (June 28, 2023): 162–67. http://dx.doi.org/10.54097/fbem.v9i3.9578.
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This paper introduces the AHP, entropy value method, TOPSIS method and fuzzy comprehensive evaluation method in the comprehensive evaluation method, and analyzes the advantages and disadvantages of the four from the perspectives of subjectivity and objectivity, acceptance of decision makers, and difficulty of evaluation. The value method depends on the amount of initial data, the AHP research results are too subjective, the TOPSIS research conclusions do not fit the reality, and the results of the fuzzy comprehensive evaluation may have poor resolution. Finally, suggestions are put forward for the application scope of the four methods of single use and combined use. It is believed that the four evaluation methods can be combined in pairs or three, such as: entropy weight-TOPSIS, AHP-TOPSIS or entropy weight-AHP -Methods such as fuzzy comprehensive evaluation method avoid being affected by the limitations of a single evaluation method.
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Li, Cheng Hua, Yun Xiu Sai, and Hui Mao. "Designing and Evaluating Safety Accident Emergency Management for Construction Project under Fuzzy Environment." Advanced Materials Research 243-249 (May 2011): 6307–11. http://dx.doi.org/10.4028/www.scientific.net/amr.243-249.6307.
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Recently, safety accident emergency management of construction project is an important issue not only for investors and governments but also for the companies that are in construction industry. Designing and evaluating safety accident emergency management is also crucial for the same sector’s development. Proposed method is based on fuzzy TOPSIS, which combined TOPSIS with triangular fuzzy numbers both in the rating of alternative and the weight of criterion. The closeness coefficient under fuzzy environment is calculated by using the concept of fuzzy positive-ideal solution and fuzzy negative-ideal solution. Then the rankings of the projects are determined according to their results.
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Baharsyah, Jhondy, Muliadi Muliadi, and Dwi Kartini. "FUZZY ANALYTICAL HIERARCHY PROCESS TOPSIS UNTUK SELEKSI PADA ANGGOTA PASKIBRAKA." KLIK - KUMPULAN JURNAL ILMU KOMPUTER 3, no. 2 (October 5, 2016): 156. http://dx.doi.org/10.20527/klik.v3i2.52.
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<p align="center"><strong>Abstract</strong></p><p><em>Every year Indonesia to conduct the selection of students and high school students and above to be representative of their school as troops heritage flag raisers. During the assessment process for the selection of candidates for members Paskibraka done manually on paper and separate between the assessment criteria for the other criteria, then the assessment results are stored in the form of an excel file. To facilitate the assessment process then takes a decision support system for the selection of candidates for members Paskibraka by applying Fuzzy AHP TOPSIS. Fuzzy AHP TOPSIS method is a convenient method to solve the problem of multi-criteria taking into account the values of the existing criteria. Thus the necessary decision support system using Fuzzy AHP TOPSIS method, in order to help provide recommendations for the decision of selectors prospective team members Paskibraka.</em></p><p><strong><em>Keywords</em></strong><strong><em> </em></strong><em>: Fuzzy AHP TOPSIS, Decision Support Systems, Selection</em></p><p><em><br /></em></p><p align="center"><strong>Abstrak</strong></p><p><em>Setiap tahun indonesia melakukan seleksi siswa dan siswi sekolah menengah keatas untuk menjadi perwakilan sekolah mereka sebagai pasukan pengibar bendera pusaka (paskibraka). Selama ini proses penilaian untuk seleksi calon anggota paskibraka dilakukan secara manual di atas kertas dan terpisah antara penilaian untuk kriteria yang satu dengan kriteria yang lainnya, kemudian hasil penilaian tersebut disimpan dalam bentuk file excel. Untuk mempermudah proses penilaian tersebut maka dibutuhkan suatu sistem pendukung keputusan untuk seleksi calon anggota paskibraka dengan menerapkan metode Fuzzy AHP Topsis. Metode Fuzzy AHP Topsis merupakan salah satu metode yang mudah digunakan untuk menyelesaikan masalah multi kriteria dengan memperhitungkan nilai-nilai dari kriteria yang ada. Maka dari itu diperlukan sistem pendukung keputusan menggunakan metode Fuzzy AHP Topsis, supaya dapat membantu memberikan rekomendasi keputusan untuk tim penyeleksi calon anggota paskibraka.</em></p><p><strong><em>Kata kunci</em></strong><em> : </em><em>Fuzzy AHP Topsis, Sistem Pendukung Keputusan, Seleksi</em></p>
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Ouma, Yashon O., J. Opudo, and S. Nyambenya. "Comparison of Fuzzy AHP and Fuzzy TOPSIS for Road Pavement Maintenance Prioritization: Methodological Exposition and Case Study." Advances in Civil Engineering 2015 (2015): 1–17. http://dx.doi.org/10.1155/2015/140189.
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For road pavement maintenance and repairs prioritization, a multiattribute approach that compares fuzzy Analytical Hierarchy Process (AHP) and fuzzy Technique for Order Preference by Ideal Situation (TOPSIS) is evaluated. The pavement distress data was collected through empirical condition surveys and rating by pavement experts. In comparison to the crisp AHP, the fuzzy AHP and fuzzy TOPSIS pairwise comparison techniques are considered to be more suitable for the subjective analysis of the pavement conditions for automated maintenance prioritization. From the case study results, four pavement maintenance objectives were determined as road safety, pavement surface preservation, road operational status and standards, and road aesthetics, with corresponding depreciating significance weights ofW=0.37,0.31,0.22,0.10T. The top three maintenance functions were identified as Thin Hot Mix Asphalt (HMA) overlays, resurfacing and slurry seals, which were a result of pavement cracking, potholes, raveling, and patching, while the bottom three were cape seal, micro surfacing, and fog seal. The two methods gave nearly the same prioritization ranking. In general, the fuzzy AHP approach tended to overestimate the maintenance prioritization ranking as compared to the fuzzy TOPSIS.
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Zhang, Huiyuan, Guiwu Wei, and Cun Wei. "TOPSIS method for spherical fuzzy MAGDM based on cumulative prospect theory and combined weights and its application to residential location." Journal of Intelligent & Fuzzy Systems 42, no. 3 (February 2, 2022): 1367–80. http://dx.doi.org/10.3233/jifs-210267.
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Nowadays, how to choose a comfortable and relatively satisfactory residence is one of the multiple attribute group decision making (MAGDM) issues which people are paying more and more attention. However, since the inaccuracy and fuzziness of the information are given by decision makers (DMs) in practical decision-making and psychological factors of DMs should be considered in the decision-making process, this paper presents TOPSIS approach based on cumulative prospect theory (CPT) to deal with the MAGDM issues under the spherical fuzzy environment. Furthermore, considering the objective relationship between the attributes, the combined weights are used to get attribute weights in spherical fuzzy sets (SFSs). Finally, an example of residential location is introduced to prove the validity of our proposed approach by comparing with spherical fuzzy TOPSIS(SF-TOPSIS) method and spherical fuzzy WASPAS (SF-WASPAS) method.
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Praningki, Tutus, Muhaji Bayu, and Agus Pramono. "Sistem Pendukung Keputusan Seleksi Atlet Panahan menggunakan Logic Fuzzy metode AHP-TOPSIS." CAHAYAtech 8, no. 2 (September 5, 2019): 150. http://dx.doi.org/10.47047/ct.v8i2.51.
Full textAbstract:
Panahan adalah cabang olahraga di induk organisasi PERPANI. Pelatihan yang dibentuk guna mencitakan atlet panaha terbaik dalam perkembangannya selalu berudaha mengikuti kejuaraan dengan langkah pelatihan atlet panahan secara teratur. Proses seleksi atlet pada PERPANI dinilai masih manual dan belum terperinci. Dalam penilaian yang bersifat subjektif (berdasarkan kepentingan pribadi), dapat menimbulkan kecemburuan pada proses penyeleksian seorang atlet. Diperlukan sebuah sistem guna membantu solusi tersebut, sistem dengan Logic Fuzzy metode AHP-TOPSIS dipilih untuk menyeleksi atlet panahan. Penulis menggunakan 6 kriteria dan 24 subkriteria dalam sistem. Proses penentuan bobot kriteria menggunakan Logic Fuzzy pada perhitungannya. Penelitian ini menggunakan Bahasa perograman PHP dan menggunakan MySQL sebagai basisdatanya. Penelitian ini berhasil memberikan hasil sistem pendukung keputusan menggunakan Logic Fuzzy metode AHP-TOPSIS mampu mengatasi permasalah dalam melakukan seleksi atlet panahan. Kata Kunci: MySQL, Seleksi Atlet Panahan, PHP, Logic Fuzzy, AHP-TOPSIS
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Alguliyev, Rasim M., Ramiz M. Aliguliyev, and Rasmiyya S. Mahmudova. "A Fuzzy TOPSIS+Worst-Case Model for Personnel Evaluation Using Information Culture Criteria." International Journal of Operations Research and Information Systems 7, no. 4 (October 2016): 38–66. http://dx.doi.org/10.4018/ijoris.2016100102.
Full textAbstract:
Personnel evaluation process is aimed at choosing the best alternative to fill the defined vacancy in an organization. It determines the input quality of personnel and thus plays an important role in human resource management. The multi criteria nature and the presence of qualitative factors make it considerably more complex. This paper proposes a hybrid fuzzy MCDM model for personnel evaluation. It combines the fuzzy TOPSIS method with fuzzy worst-case (or entropy) method for linguistic reasoning under group decision making. Fuzzy worst-case and entropy methods are used to get weights of criteria, while fuzzy TOPSIS is utilized to rank the alternatives. The weights obtained from fuzzy worst-case and entropy methods are included in fuzzy TOPSIS computations and the alternatives are evaluated. The fuzzy MCDM for group decision making enables to aggregate subjective assessments of the decision-makers and thus offer an opportunity to perform more robust personnel evaluation procedures. To evaluate the alternatives the authors have formed an executive group consisting of five decision-makers. For evaluation the group has decided to consider five information culture criteria expressed in linguistic variables. A numerical example demonstrated the possibilities of application of the proposed method.
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Anisseh, Mohammad, Fatemeh Hemmati, and Reza Shahraki. "Best selection of project portfolio using Fuzzy AHP and Fuzzy TOPSIS." Journal of Engineering Management and Competitiveness 8, no. 1 (2018): 3–10. http://dx.doi.org/10.5937/jemc1801003a.
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