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Journal articles on the topic 'TOPSIS'
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1
Su, Jiahui, and Yidi Sun. "An Improved TOPSIS Model Based on Cumulative Prospect Theory: Application to ESG Performance Evaluation of State-Owned Mining Enterprises." Sustainability 15, no. 13 (June 25, 2023): 10046. http://dx.doi.org/10.3390/su151310046.
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The aim of this study is to provide a comprehensive decision-making method that can be applied to investment decisions based on the Environmental, Social and Governance (ESG) performance. The study contributes to the existing literature by introducing the CPT-TOPSIS model, a pioneering approach that incorporates the effect of non-rational factors on decision-making results in uncertain conditions by combining cumulative prospect theory (CPT) with the classic TOPSIS model. Moreover, by conducting an application to ESG evaluation on five state-owned mining enterprises in China, the study provides evidence of the effectiveness and improvement offered by the new model in comparison with the classic TOPSISI model and prospect theory TOPSIS (PT-TOPSIS) model. The results suggest that the CPT-TOPSIS model considers risk preferences and probability distortion in the decision-making process, narrows the gap between ESG scores, and makes ESG performance evaluation more realistic.
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Maharani, Septya, Holis Ridwanto, Heliza Rahmania Hatta, Dyna Marisa Khairina, and Muhammad Rivani Ibrahim. "Comparison of TOPSIS and MAUT methods for recipient determination home surgery." IAES International Journal of Artificial Intelligence (IJ-AI) 10, no. 4 (December 1, 2021): 930. http://dx.doi.org/10.11591/ijai.v10.i4.pp930-937.
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<span lang="EN-US">House renovation is given by the government to the community, one of which is the assistance provided in the district. Long Mevery especially Tanah Abang Village, namely House Renovation Assistance. So it is necessary to implement a DSS in determining the recipient of home renovation assistance by comparing MAUT method and TOPSIS to assist the government in determining the right home renovation assistance recipient. There are 16 criteria and their weight values. This study uses the multi-attribute utility theory method (MAUT) and the order of preference technique based on the similarity to the ideal solution (TOPSI) as a calculation method to produce output and determine the level of accuracy of each method. The test in this study uses a confusion matrix and compares real data testing with the results of calculations on the system. The results of system testing using MAUT and TOPSIS methods, the accuracy of the MAUT method is 94.28% and the TOPSIS method is 35.71%.</span>
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Yu, Liping, Wenhua Yang, Yunlong Duan, and Xinwen Long. "A Study on the Application of Coordinated TOPSIS in Evaluation of Robotics Academic Journals." Mathematical Problems in Engineering 2018 (July 11, 2018): 1–7. http://dx.doi.org/10.1155/2018/5456064.
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While TOPSIS is a widely used evaluation method, it lacks evaluation from the perspective of indicator coordination. Based on the analysis of TOPSIS evaluation methods, this paper proposes a new assessment method, coordinated TOPSIS, which takes into account the advantages of TOPSIS evaluation methods and the coordination level of evaluation indicators. Taking the robotics academic journals as an example, the TOPSIS evaluation and the coordinated TOPSIS evaluation results are compared. The research shows that the weights of the coordinated TOPSIS method can be manually adjusted according to the purpose of evaluation and have a good flexibility; the TOPSIS evaluation results and coordinated TOPSIS evaluation results have a high degree of correlation, but the difference from the perspective of the ranking is big; the coordinated TOPSIS is very suitable for evaluation field that needs to consider the coordinated development, and it can be replicated.
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Chen, Pengyu. "A Novel Coordinated TOPSIS Based on Coefficient of Variation." Mathematics 7, no. 7 (July 11, 2019): 614. http://dx.doi.org/10.3390/math7070614.
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Coordinated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a significant improvement of TOPSIS, which take into account the coordination level of attributes in the decision-making or assessment. However, in this study, it is found that the existing coordinated TOPSIS has some limitations and problems, which are listed as follows. (1) It is based on modified TOPSIS, not the original TOPSIS. (2) It is inapplicable when using vector normalization. (3) The calculation formulas of the coordination degree are incorrect. (4) The coordination level of attributes is interrelated with the weights. In this paper, the problems of the existing coordinated TOPSIS are explained and revised, and a novel coordinated TOPSIS based on coefficient of variation is proposed to avoid the limitations. Comparisons of the existing, revised, and proposed coordinated TOPSIS are carried out based on two case studies. The comparison results validate the feasibility of the proposed coordinated TOPSIS.
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Chakraborty, Subrata. "TOPSIS and Modified TOPSIS: A comparative analysis." Decision Analytics Journal 2 (March 2022): 100021. http://dx.doi.org/10.1016/j.dajour.2021.100021.
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Dewi, Ratih Kartika. "Group Decision Support System based on AHP-TOPSIS for Culinary Recommendation System." Jurnal Ilmu Komputer dan Informasi 12, no. 2 (July 8, 2019): 85. http://dx.doi.org/10.21609/jiki.v12i2.729.
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This paper proposes the integration of AHP and TOPSIS to generate the ranking results of culinary recommendation for a group of users to provide better recommendation results. Formerly, Group Decision Support System (GDSS) for culinary recommendations has been developed with the TOPSIS method. TOPSIS has low algorithm complexity, so it is suitable to be applied in mobile devices. However, GDSS with TOPSIS has its disadvantages, TOPSIS have not been able to facilitate the preferences of each user inside a group so the recommendation result always consist only on dominant user. TOPSIS method produces unchanging rankings, because this method recommends a food menu based on the 1 dominant user so that the ranking is always consistent. Meanwhile, this study aims to integrate AHP for weighting criteria from each user and TOPSIS for ranking culinary recommendations. Based on rank consistency testing results that conducted in 6 different user groups, unlike the previous research, AHP-TOPSIS shows inconsistency ranking, which means that changes in user preferences affect the recommendation results that are generated by application. The AHP-TOPSIS method proved can be accommodated the computation of various preferences of each user in GDSS culinary recommendation
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Dewi, Ratih Kartika, Eriq Muhammad Adams Jonemaro, Agi Putra Kharisma, Najla Alia Farah, and Mury Fajar Dewantoro. "TOPSIS for mobile based group and personal decision support system." Register: Jurnal Ilmiah Teknologi Sistem Informasi 7, no. 1 (February 15, 2021): 43. http://dx.doi.org/10.26594/register.v7i1.2140.
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Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is an algorithm that can be used for alternative design in a decision support system (DSS). TOPSIS provides recommendation so that users can get information that support their decision, for example a tourist wants to visit a tourist destination in Malang, then TOPSIS provides recommendations of tourist destinations in the form of ranking recommendation, with the highest rank is the most recommended recommendation. TOPSIS-based Mobile Decision Support System (DSS) has relatively low algorithm complexity. However, there are some cases that require development from personal DSS to group DSS, for example tourists rarely come alone, in which case most of them invite friends or family. For users who are more than 1 person, the TOPSIS algorithm can be combined with the BORDA algorithm. This study explains about the implementation & testing of TOPSIS and TOPSIS-BORDA as algorithms for personal and group DSS in mobile-based tourism recommendation system in Malang. Correlation testing was conducted to test the effectiveness of TOPSIS in mobile-based recommendation system. In previous study, correlation testing for personal DSS showed that there was a relationship between the recommendation and user choice, with correlation value of 0.770769231. In this study, correlation testing for group DSS showed there is a positive correlation of 0.88 between the recommendations of the group produced by TOPSIS-BORDA and personal recommendations for each user produced by TOPSIS.
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Quan, Huafeng, Shaobo Li, Hongjing Wei, and Jianjun Hu. "Personalized Product Evaluation Based on GRA-TOPSIS and Kansei Engineering." Symmetry 11, no. 7 (July 3, 2019): 867. http://dx.doi.org/10.3390/sym11070867.
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With the improvement of human living standards, users’ requirements have changed from function to emotion. Helping users pick out the most suitable product based on their subjective requirements is of great importance for enterprises. This paper proposes a Kansei engineering-based grey relational analysis and techniques for order preference by similarity to ideal solution (KE-GAR-TOPSIS) method to make a subjective user personalized ranking of alternative products. The KE-GRA-TOPSIS method integrates five methods, including Kansei Engineering (KE), analytic hierarchy process (AHP), entropy, game theory, and grey relational analysis-TOPSIS (GRA-TOPSIS). First, an evaluation system is established by KE and AHP. Second, we define a matrix variate—Kansei decision matrix (KDM)—to describe the satisfaction of user requirements. Third, the AHP is used to obtain subjective weight. Next, the entropy method is employed to obtain objective weights by taking the KDM as input. Then the two types of weights are optimized using game theory to obtain the comprehensive weights. Finally, the GRA-TOPSIS method takes the comprehensive weights and the KMD as inputs to rank alternatives. A comparison of the KE-GRA-TOPSIS, KE-TOPSIS, KE-GRA, GRA-TOPSIS, and TOPSIS is conducted to illustrate the unique merits of the KE-GRA-TOPSIS method in Kansei evaluation. Finally, taking the electric drill as an example, we describe the process of the proposed method in detail, which achieves a symmetry between the objectivity of products and subjectivity of users.
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Okul, Deniz, Cevriye Gencer, and Emel Kizilkaya Aydogan. "A Method Based on SMAA-Topsis for Stochastic Multi-Criteria Decision Making and a Real-World Application." International Journal of Information Technology & Decision Making 13, no. 05 (September 2014): 957–78. http://dx.doi.org/10.1142/s0219622014500175.
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Stochastic multi-criteria acceptability analysis (SMAA-2) and the technique for order preference by similarity to ideal solution (TOPSIS) are methods for evaluating alternatives with multiple criteria. SMAA is a method that is used for solving multi-criteria decision-making problems with uncertain, inaccurate information, and does not require preference information from the decision makers. The TOPSIS method is based on the principle of determining a solution with the shortest distance to the ideal solution and the greatest distance from the negative-ideal solution. This paper proposes a new method, SMAA-TOPSIS, by combining the SMAA and TOPSIS methods. The SMAA-TOPSIS method was executed for two problems: drug benefit-risk analysis and machine gun selection. This paper found that TOPSIS could be used with uncertain and arbitrarily distributed values for weights and criteria measurements by using a combination of SMAA and TOPSIS. Also, we obtained clearer and consistent SMAA outputs.
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Zavadskas, Edmundas Kazimieras, Abbas Mardani, Zenonas Turskis, Ahmad Jusoh, and Khalil MD Nor. "Development of TOPSIS Method to Solve Complicated Decision-Making Problems — An Overview on Developments from 2000 to 2015." International Journal of Information Technology & Decision Making 15, no. 03 (May 2016): 645–82. http://dx.doi.org/10.1142/s0219622016300019.
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In recent years several previous scholars made attempts to develop, extend, propose and apply Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for solving problems in decision making issues. Indeed, there are questions, how TOPSIS can help for solving these problems? Or does TOPSIS solved decision making problems in the real world? Therefore, this study shows the recent developments of TOPSIS approach which are presented by previous scholars. To achieve this objective, there are 105 reviewed papers which developed, extended, proposed and presented TOPSIS approach for solving DM problems. The results of the study indicated that 49 scholars have extended or developed TOPSIS technique and 56 scholars have proposed or presented new modifications for problems solution related to TOPSIS technique from 2000 to 2015. In addition, results of this study indicated that, previous studies have modifications related to this technique in 2011 more than other years.
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Quynh, Vu Thi Nhu. "An extension of TOPSIS method using interval bipolar linguistic neutrosophic set and its application." Multidisciplinary Science Journal 5, no. 4 (June 3, 2023): 2023045. http://dx.doi.org/10.31893/multiscience.2023045.
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TOPSIS, known as the “Technique for Order of Preference by Similarity to Ideal Solution” (TOPSIS), is one of the well-known methods for solving “multi-criteria decision-making” (MCDM) problems. Many TOPSIS methods have been developed to solve real-life problems using neutrosophic sets. However, no study has developed the TOPSIS method under interval bipolar linguistic neutrosophic environments. Therefore, this study aims to present a new concept of “interval bipolar linguistic neutrosophic set” (IBL_NS). IBL_NS is more flexible and adaptable to real-world applications than other sets. Some set-theoretic operations, such as “union”, “intersection”, and “complement”, and the “operational rules” of IBL_NS are defined. Then, a new TOPSIS procedure in IBL_NS is developed. In the proposed IBL_NS-TOPSIS method, ratings of alternatives and importance weights of criteria are expressed in IBL_NS. An application is presented demonstrating the advantages of the proposed IBL_NS-TOPSIS approach.
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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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Yang, Wenguang. "Ingenious Solution for the Rank Reversal Problem of TOPSIS Method." Mathematical Problems in Engineering 2020 (January 30, 2020): 1–12. http://dx.doi.org/10.1155/2020/9676518.
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Although the classic TOPSIS method is very practical, there may be a problem of rank reversal in the addition, deletion, or replacement of the candidate set, which makes its credibility greatly compromised. Based on the understanding of the classical TOPSIS method, this paper establishes a new improved TOPSIS method called NR-TOPSIS. Firstly, the historical maximum and minimum values of all attribute indicators from a global perspective during the evaluation process are determined. Secondly, according to whether the attributes belong to the benefit attribute or cost attribute, standardization is carried out. And then, in the case where the historical values of attributes are determined, we re-fix the positive ideal solution and the negative ideal solution. At the same time, this paper gives the definition of ranking stable and proves that the NR-TOPSIS proposed satisfies ranking stable, which theoretically guarantees that the rank reversal phenomenon does not exist. Finally, in the verification of examples, the results are consistent with the theoretical analysis, which further support the theoretical analysis. The NR-TOPSIS method overcomes rank reversal, which is not only obviously superior to the classical TOPSIS method but also relatively superior to the R-TOPSIS method which has also overcome rank reversal. It is also superior to other reference methods due to its simple calculation.
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Fei, Liguo, Yong Hu, Fuyuan Xiao, Luyuan Chen, and Yong Deng. "A Modified TOPSIS Method Based onDNumbers and Its Applications in Human Resources Selection." Mathematical Problems in Engineering 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/6145196.
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Multicriteria decision-making (MCDM) is an important branch of operations research which composes multiple-criteria to make decision. TOPSIS is an effective method in handling MCDM problem, while there still exist some shortcomings about it. Upon facing the MCDM problem, various types of uncertainty are inevitable such as incompleteness, fuzziness, and imprecision result from the powerlessness of human beings subjective judgment. However, the TOPSIS method cannot adequately deal with these types of uncertainties. In this paper, aD-TOPSIS method is proposed for MCDM problem based on a new effective and feasible representation of uncertain information, calledDnumbers. TheD-TOPSIS method is an extension of the classical TOPSIS method. Within the proposed method,Dnumbers theory denotes the decision matrix given by experts considering the interrelation of multicriteria. An application about human resources selection, which essentially is a multicriteria decision-making problem, is conducted to demonstrate the effectiveness of the proposedD-TOPSIS method.
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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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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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Zhan, Qiuyan, Lesheng Jin, and Ronald R. Yager. "A Modified TOPSIS Approach with Three-Way Decision." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 31, no. 05 (October 2023): 795–823. http://dx.doi.org/10.1142/s021848852350037x.
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In real life, multiple attribute decision problems (MADM) can be applied in different areas and numerous related extensions and methodologies have been proposed by researchers. Combining three-way TOPSIS decision ideas with MADM is a feasible and meaningful research direction. In light of this, this paper generalizes the classical TOPSIS method with the help of mean and standard deviation and proposes the so-called modified three-way TOPSIS. First, using a pair of thresholds which is derived by mean and standard deviation, we divide decision alternatives into three segments, and then a preliminary rank results of decision alternatives can be obtained. Furthermore, in each decision region, we use two ranking regulations (one-way TOPSIS or modified two-way TOPSIS method) to rank decision alternatives. A practical example of urban expressway route selection illustrates the feasibility of the proposed method. Finally, we test the feasibility and validity of the modified three-way TOPSIS method by comparing with some existing method.
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Azizsyah, Silviah Noor, and Desi Pibriana. "Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Pada Pt Segara Makmur Sejahtera Menggunakan Metode Topsis." COMSERVA : Jurnal Penelitian dan Pengabdian Masyarakat 3, no. 06 (October 26, 2023): 2418–41. http://dx.doi.org/10.59141/comserva.v3i06.1027.
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Penilaian kinerja karyawan merupakan langkah penting bagi perusahaan. Penelitian ini bertujuan untuk mengatasi masalah evaluasi karyawan di PT Segara Makmur Sejahtera. Penelitian ini menggunakan metode TOPSIS pada Sistem Pendukung Keputusan (SPK) untuk menentukan karyawan terbaik. Hasil wawancara dengan HRD perusahaan menunjukkan adanya permasalahan dalam penilaian karyawan yang tidak adil dan proses penilaian yang lambat. Metode TOPSIS dipilih berdasarkan kesederhanaan dan keberhasilan penelitian sebelumnya. Dalam perhitungan perusahaan, penilaian karyawan didasarkan pada penilaian tanpa bobot, sedangkan TOPSIS memberikan bobot pada kriteria penilaian. Hasil pemeringkatan dari kedua metode tersebut berbeda, menunjukkan keadilan komputasi yang lebih baik menggunakan TOPSIS. Oleh karena itu, penelitian ini mengusulkan implementasi SPK menggunakan metode TOPSIS dengan metodologi pengembangan sistem menggunakan Rational Unified Process untuk mempercepat pengambilan keputusan dalam pemilihan karyawan terbaik di perusahaan.
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Isabella Ester Eka Sandaa, Amida Sekar Kinasih Tanatti, Andreas Haryono, and Soetam Rizky Wicaksono. "Analisis Pengadaaan Tender Kebutuhan Aplikasi (Software) Menggunakan Metode TOPSIS." Journal of Computers and Digital Business 1, no. 2 (September 30, 2022): 37–46. http://dx.doi.org/10.56427/jcbd.v1i2.8.
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Pemerintah kota surabaya merencanakan pengadaaan Tender kebutuhan software. Dalam penelitian ini akan menggunakan metode TOPSIS dalam sistem pendukung keputusan untuk menentukan pengadaan Tender kebutuhan aplikasi di pemerintah kota surabaya. Berdasarkan metode TOPSIS maka hasil yang diperoleh dari penelitian ini adalah bahwa dengan menggunakan metode TOPSIS dapat membantu dalam menerapkan sistem pendukung keputusan pengadaan tender kebutuhan aplikasi. Penerapan metode TOPSIS ini membuahkan sebuah hasil dalam aplikasi sistem pendukung keputusan yang dimana memperoleh hasil yang lebih akurat sehingga dapat membantu menentukan pengadaan tender kebutuhan aplikasi pada kota Surabaya.
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Kahraman, Cengiz, Selcuk Cebi, Basar Oztaysi, and Sezi Cevik Onar. "Intuitionistic Fuzzy Sets with Ordered Pairs and Their Usage in Multi-Attribute Decision Making: A Novel Intuitionistic Fuzzy TOPSIS Method with Ordered Pairs." Mathematics 11, no. 18 (September 10, 2023): 3867. http://dx.doi.org/10.3390/math11183867.
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Intuitionistic Fuzzy Sets with Ordered Pairs (IFSOP) are the recent extension of intuitionistic fuzzy sets by incorporating functional and dysfunctional points of view into the definition of membership functions. This paper extends the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) method to the Intuitionistic Fuzzy TOPSIS (IF TOPSIS) with ordered pairs method and applies it to a multi-criteria risk-based supplier selection problem under fuzziness. IF TOPSIS with ordered pairs involves finding a positive ideal solution and a negative ideal solution, and measuring the distance between each alternative and these solutions. The final ranking of the alternatives is obtained based on the proportion of distances between the positive and negative ideal solutions. By asking functional and dysfunctional questions in this ranking process, the developed IF TOPSIS with ordered pairs method incorporates the accuracy and consistency of expert judgments, enhancing the decision-making process. A sensitivity analysis is also presented in order to show the robustness of the rankings obtained by IF TOPSIS with ordered pairs.
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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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Yang, Wenguang, and Yunjie Wu. "A Novel TOPSIS Method Based on Improved Grey Relational Analysis for Multiattribute Decision-Making Problem." Mathematical Problems in Engineering 2019 (February 4, 2019): 1–10. http://dx.doi.org/10.1155/2019/8761681.
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Multiattribute decision-making (MADM) problem is difficult to assess because of the large number of attribute indices and the diversity of data distribution. Based on the understanding of data dispersion degree, a new grey TOPSIS method for MADM is studied. The main idea of this paper is to redefine the grey relational analysis through the dispersion of data distribution and redesign the TOPSIS by using the improved grey relational analysis. As a classical multiattribute decision analysis method, traditional TOPSIS does not consider the data distribution of the degree of dispersion and aggregation when it is compared with the optimal and worst alternative solutions. In view of the limitations of traditional TOPSIS, this paper has made two major improvements to TOPSIS. Firstly, the new grey relational analysis is applied to evaluate the grey positive relational degree between each alternative and the optimal solution and compute the grey negative relational degree between each alternative and the worst solution. Secondly, the weights of every attribute index about the optimal and worst solutions are put forward based upon the distance standard deviation and the average distance. Finally, the comprehensive grey TOPSIS is utilized to analyze the ranking of weapon selection problem. The numerical results verify the feasibility of the improved grey relational analysis and also highlight the practicability of the grey comprehensive TOPSIS.
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Li, Qian. "Weighted absolute degree of grey incidence with TOPSIS and its application." Grey Systems: Theory and Application 6, no. 2 (August 1, 2016): 281–91. http://dx.doi.org/10.1108/gs-11-2015-0074.
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Purpose – The purpose of this paper is to evaluate and rank the influence of internet public opinion of China’s Government work in 2015 by weighted absolute degree of grey incidence with TOPSIS. Design/methodology/approach – This disaggregation method includes four main steps, determine the vector of weights for the factors by analytic hierarchy process, calculate the matrix of consistent effect measure, determine the weighted absolute degree of grey incidence with TOPSIS, rank and evaluate the events. Findings – We get the ranking of internet public opinion of China’s Government work in 2015 by weighted absolute degree of grey incidence with TOPSIS. The result can be used for evaluating and ranking the influence of internet public opinion in China. The positive weighted absolute degree of grey incidence, the negative weighted absolute degree of grey incidence and the weighted absolute degree of grey incidence with TOPSIS have the same ranking results. The same ranking results show that the method of weighted absolute degree of grey incidence with TOPSIS has good consistency. Practical implications – The weighted absolute degree of grey incidence with TOPSIS can be easily used for other evaluation. Originality/value – The weighted absolute degree of grey incidence with TOPSIS is proposed and first used for evaluating and ranking the influence of internet public opinion of China’s Government work.
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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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Hajar, Muhammad Hafizd Ibnu, Galang Persada Nurani Hakim, Ahmad Firdausi, and Eko Ramadhan. "Comparison in Quality of service Performance For Wireless Sensor Network Routing between Fuzzy Topsis and SAW Algorithm." Jurnal Informatika: Jurnal Pengembangan IT 6, no. 2 (May 31, 2021): 114–18. http://dx.doi.org/10.30591/jpit.v6i2.2530.
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one of the advantages of Wireless Sensor Network would be its ability to reduce cost of communication system using node to node communication. Because of many things data transfer is Wireless Sensor Network operation sometimes has disturbance. A routing algorithm is a network coding that intends to enhance network performance for better operation with or without any disturbance. Fuzzy TOPSIS and SAW as MCDM algorithm is proposed for routing algorithm in Wireless Sensor Network operation. From our simulation both SAW and Fuzzy Topsis algorithm can be used in network coding (routing) to provide better QOS for Wireless Sensor Network compare with shortest path routing. For delay it perform better at about 2/3 (shortest path routing 50 millisecond, both SAW and Fuzzy Topsis algorithm 33 millisecond), and for packet loss at about 3/4 (shortest path routing 21 bit loss, both SAW and Fuzzy Topsis algorithm 16 bit loss). From our simulation both SAW and Fuzzy Topsis algorithm algorithm has benefit which is lower delay and packet loss but at higher cost which is more hopping for communication channel (shortest path routing 3 hopping, both SAW and Fuzzy Topsis algorithm 5 hopping)
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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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Peng, Cheng, Dianzhuang Feng, and Sidai Guo. "Material Selection in Green Design: A Method Combining DEA and TOPSIS." Sustainability 13, no. 10 (May 14, 2021): 5497. http://dx.doi.org/10.3390/su13105497.
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In order to rationalize material selection in green design, this study presents an attempt to combine the methods of generalized Data Envelopment Analysis (DEA) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). By establishing a green material index system, the G-CCR model of generalized DEA was first used to select effective materials from the candidate samples, and TOPSIS was then used to sort the effective suppliers. The combined DEA/TOPSIS model helps to rank the materials by quality, and then integrate both the merits ofG-CCR model and the key characteristics of TOPSIS. The results of this study showed that the combined DEA/TOPSIS model can screen and exclude materials with poor performance when selecting wood for the furniture industry. Therefore, the combined model that is presented in this study provides a more rational and evidentiary basis for material selection in green design.
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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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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.
Full textAbstract:
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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M. Saeed, Z Anam, T. Kanwal, I. Saba, F. Memoona, and M. F. Tabassum. "Generalization of TOPSIS from Soft Set to Fuzzy Soft Sets in Decision Making Problem." Scientific Inquiry and Review 1, no. 1 (November 7, 2017): 11–18. http://dx.doi.org/10.32350/sir/11/010102.
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As of late, the issue of basic decision making has discovered imperative centrality. It has procured central significance particularly for the issues identified with incorrect environment. The technique for order of preference by similarities to ideal solution (TOPSIS) is the multi criteria choice examining technique utilized for the choice. We apply the generalized result of TOPSIS on soft set to TOPSIS on fuzzy-soft-set.
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Yoon, K. Paul, and Won Kyung Kim. "The behavioral TOPSIS." Expert Systems with Applications 89 (December 2017): 266–72. http://dx.doi.org/10.1016/j.eswa.2017.07.045.
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Silva, Marcela do Carmo, Carlos Francisco Simões Gomes, and Reinaldo Castro Souza. "TOPSIS-2NE’s Proposal." International Journal of Fuzzy Systems 22, no. 4 (May 7, 2020): 1118–22. http://dx.doi.org/10.1007/s40815-020-00871-4.
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Lai, Young-Jou, Ting-Yun Liu, and Ching-Lai Hwang. "TOPSIS for MODM." European Journal of Operational Research 76, no. 3 (August 1994): 486–500. http://dx.doi.org/10.1016/0377-2217(94)90282-8.
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Sufarnap, Erlanie, and Sudarto -. "Perbandingan Metode Pengambilan Keputusan pada Pemilihan Hotel Berbasis SAW dan TOPSIS." Jurnal SIFO Mikroskil 23, no. 1 (April 28, 2022): 73–82. http://dx.doi.org/10.55601/jsm.v23i1.850.
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Dalam mencari hotel terbaik tentunya memiliki beberapa kendala dalam pencarian hotel berdasarkan kriteria yang sesuai dengan kebutuhan pengguna. Penelitian ini bertujuan untuk memudahkan pengguna dalam mencari hotel yang sesuai dengan kebutuhan mereka dengan menggunakan metode SAW dan TOPSIS sebagai sarana untuk memudahkan pencarian hotel yang dapat menghitung nilai bobot dari tiap-tiap kriteria yang telah ditentukan oleh peneliti. Adapun hasil eksperimen atau pengujian yang telah dilakukan menunjukkan bahwa untuk perangkingan alternatif A4 memiliki nilai terbesar sehingga menjadi alternatif terbaik di metode SAW dan TOPSIS A4 memiliki nilai terbesar sehingga menjadi alternatif terbaik. Untuk persentase perubahan perangkingan pada metode SAW sebesar 0,54 sedangkan untuk metode TOPSIS sebesar 0,342215202 pertambahan bobot 0,5 sedangkan untuk pertambahan bobot 1 untuk metode SAW sebesar 1,46 untuk TOPSIS sebesar 0,507599707.??? Hasil perbandingan eksperimen ini menunjukkan bahwa hasil yang didapatkan metode SAW lebih besar daripada metode TOPSIS sehingga metode SAW menjadi metode yang relevan untuk menyelesaikan kasus seleksi pemilihan hotel.
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Tahyudin, Imam, Rahman Rosyidi, Ansari Saleh Ahmar, and Haviluddin . "Comparison of the Simple Additive Weighting (SAW) with the Technique for Others Reference by Similarity to Ideal Solution (TOPSIS) methods." International Journal of Engineering & Technology 7, no. 2.2 (March 5, 2018): 87. http://dx.doi.org/10.14419/ijet.v7i2.2.12740.
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The purpose of this research is to compare the SAW and TOPSIS methods. This research uses data selection of education scholarship in an Indonesian public school. This research uses data from selection of education scholarship program in an Indonesian public school. The methods usage is SAW and TOPSIS methods. A comparison of the two methods using this data set demonstrates that SAW method was more accurate than TOPSIS method.
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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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Wang, Lin, Qiang Zu, and Qiang Zhang. "A procedure for risk assessment of check dam systems: A case study of Wangmaogou watershed." PLOS ONE 18, no. 6 (June 27, 2023): e0287750. http://dx.doi.org/10.1371/journal.pone.0287750.
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Flood-based hydrodynamic damage to check dam systems on the Loess Plateau of China occurs frequently, and there is a strong desire to carry out risk assessments of such check dam systems. This study proposes a weighting method that combines the analytic hierarchy process, entropy method, and TOPSIS to assess the risk of check dam systems. The combined weight-TOPSIS model avoids weight calculation only considers the influence of subjective or objective preference and the bias of the single weighting method. The proposed method is capable of multi-objective risk ranking. It is applied to the Wangmaogou check dam system located in a small watershed on the Loess Plateau. The result of risk ranking matches the reality of the situation. The gray correlation theory model is utilized to rank the risks in the same research area and compared with the results of the combined weight-TOPSIS model. The combined weight-TOPSIS model is more favorable to risk assessment than the gray correlation theory model. The resolution level and decisive judgment of the combined weight-TOPSIS model are more advantageous. These results are in line with the actual conditions. It proves that the combined weight-TOPSIS model can provide a technical reference for the risk assessment of check dam systems in small watersheds.
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Lukić, Radojko. "Analysis of development and effects of electronic trade in Serbia based on SF-TOPSIS and TOPSIS methods." Anali Ekonomskog fakulteta u Subotici, no. 00 (2023): 26. http://dx.doi.org/10.5937/aneksub2300023l.
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The issues of measuring and analysing the development dynamics and effects of electronic trade are currently topical, significant and complex in any country, including Serbia. In the observed period from 2017 to 2021, according to the obtained empirical results based on the SF TOPSIS method, the largest number of trading companies introducing e-business (IT technology) and e-trading appeared in Serbia in 2017. According to the obtained empirical results based on the classical TOPSIS method, the largest number of trading companies introducing e-business (IT technology) and e-trading was recorded in Serbia in 2019. The following is the ranking according to the SF-TOPSIS method: 2021, 2018, 2019 and 2020. The ranking according to the TOPSIS method is as follows: 2020, 2021, 2018 and 2017. The digitalisation factors of overall business operation of trade industry in Serbia are the global trend and requirements, degree of development of contemporary IT technology and the possibility of application in all the segments of trading operations, the economic climate, financial opportunities, entry of international retail chains, development of multichannel sale-classic and e-retail facilities, around-the clock business operations without time and geographical barriers etc. Considering the positive effects, significantly more should be invested in new information and communication technology in the future.
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Sumiatun, Sumiatun, and Kuzairi Kuzairi. "ANALISIS OPTIMAL PENJUALAN PETIS MADURA MENGGUNAKAN METODE TOPSIS." Jurnal Matematika "MANTIK" 1, no. 1 (November 18, 2015): 17. http://dx.doi.org/10.15642/mantik.2015.1.1.17-21.
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Petis merupakan jenis makanan yang digemari orang banyak, selain dijadikan bahan untuk usaha yang ditekuni, petis juga bemanfaat untuk bahan pendamping makanan rigan seperti gorengan, uniknya petis Madura ini awet dan dijual sampai keluar Madura. Dalam penelitian ini metode yang digunakan adalah Technique For Order Preference By Similarity To Ideal Solution (TOPSIS). Metode TOPSIS adalah salah satu metode yang digunakan untuk menyelesaikan masalah Multi Attribute Decision Making (MADM). Metode TOPSIS didasarkan pada konsep dimana alternatif terpilih yang terbaik tidak hanya memiliki jarak terpendek dari solusi ideal positif, namun juga memiliki jarak terpanjang dari solusi ideal negatif. Metode TOPSIS memiliki beberapa kelebihan, diantaranya konsepnya yang sederhana dan mudah dipahami, komputasinya efisien, dan memiliki kemampuan untuk mengukur kinerja relatif dari alternatif-alternatif keputusan dalam bentuk matematis yang sederhana.
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Niqotaini, Zatin. "PENERAPAN DAN PERBANDINGAN METODE AHP DAN TOPSIS UNTUK SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KARYAWAN TERBAIK." Technologia : Jurnal Ilmiah 14, no. 2 (April 1, 2023): 140. http://dx.doi.org/10.31602/tji.v14i2.10280.
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Penelitian ini bertujuan untuk mengetahui penerapan serta perbandingan metode AHP dan metode TOPSIS untuk sistem pendukung keputusan pemilihan karyawan terbaik di PT. Sukses. Kriteria yang digunakan dalam penelitian ini adalah absensi, dedikasi, disiplin, kerja sama, komunikasi, tanggung jawab. Dengan hasil uji sensitivitas dinyatakan bahwa metode AHP memiliki perubahan presentase sesitivitas yang lebih tinggi dibandingkan dengan metode TOPSIS. Hal ini terlihat pada nilai uji senstivitas metode AHP dengan presentase nilai perubahan sensitivitas sebesar 1.65344%, sedangkan pada metode TOPSIS presentase nilai perubahan sensitivitas sebesar -0.001085%. Hasil pada metode AHP alternatif yang terpilih yaitu A5 dengan nama Melly, sedangkan hasil pada metode TOPSIS alternatif yang terpilih yaitu A5 juga dengan nama Melly, diketahui bahwa metode AHP relevan untuk pemilihan karyawan terbaik di PT. Sukses.
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Pınar, Adem, Rouyendegh Babak Daneshvar, and Yavuz Selim Özdemir. "q-Rung Orthopair Fuzzy TOPSIS Method for Green Supplier Selection Problem." Sustainability 13, no. 2 (January 19, 2021): 985. http://dx.doi.org/10.3390/su13020985.
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Supply chain management is to improve competitive stress. In today’s world, competitive terms and customer sense have altered in favor of an environmentalist manner. As a result of this, green supplier selection has become a very important topic. In the green supplier selection approach, agility, lean process, sustainability, environmental sensitivity, and durability are pointed. Like the classical supplier selection problems, environmental criteria generally emphasize green supplier selection. However, these two problem approaches are different from each other in terms of carbon footprint, water consumption, environmental and recycling applications. Due to the problem structure, a resolution is defined that includes an algorithm based on q-Rung Orthopair Fuzzy (q-ROF) TOPSIS method. Brief information about q-ROF sets is given before the methodology of the q-ROF model is introduced. By using the proposed method and q-ROF sets, an application was made with today’s uncertain conditions. In the conclusion part, a comparison is made with classical TOPSIS, Intuitionistic Fuzzy TOPSIS and q-ROF TOPSIS methodology. As a result, more stable and accurate results are obtained with q-ROF TOPSIS.
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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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Ranjan, Rajeev, Abhijit Saha, and Anil Kumar Das. "Comparison of Multi-Criteria Decision Making Methods for Multi Optimization of GTAC Process Parameters." Periodica Polytechnica Mechanical Engineering 66, no. 2 (March 22, 2022): 166–74. http://dx.doi.org/10.3311/ppme.19835.
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A great deal of investigation on gas tungsten arc cladding (GTAC) is focused on the study of enhancements in the microstructure, mechanical and tribological features of the cladding. The selection of right process parameters is a critical issue for the researchers. Decision makers in the industries must analyze a wide variety of parameters based on a set of contradictory criteria. Several multi-criteria decision-making (MCDM) techniques are now available to add values in selection of these parameters. The application of the TOPSIS and MOORA techniques to identify the best configuration of processing parameters in the gas tungsten arc cladding (GTAC) process is investigated in this work. The best processing parameters set for the multiple performance attributes should be welding current: 70 amp, speed: 240, argon flow: 13 and standoff distance 3.5 (TOPSIS-PCA) and welding current: 50, speed: 300, argon flow: 13 and standoff distance 3.5 (MOORA-PCA).A comparison of MOORA-PCA and TOPSIS-PCA demonstrates the superiority of TOPSIS over MOORA technique. The prediction accuracy of the TOPSIS-PCA hybrid approach model is found better than MOORA-PCA technique.
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Bisio, Igor, and Andrea Sciarrone. "Fast Multiattribute Network Selection Technique for Vertical Handover in Heterogeneous Emergency Communication Systems." Wireless Communications and Mobile Computing 2019 (April 16, 2019): 1–17. http://dx.doi.org/10.1155/2019/8587932.
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The telecommunication infrastructure in emergency scenarios is necessarily composed of heterogeneous radio/mobile portions. Mobile Nodes (MNs) equipped with multiple network interfaces can assure continuous communications when different Radio Access Networks (RANs) that employ different Radio Access Technologies (RATs) are available. In this context, the paper proposes the definition of a Decision Maker (DM), within the protocol stack of the MN, in charge of performing network selections and handover decisions. The DM has been designed to optimize one or more performance metrics and it is based on Multiattribute Decision Making (MADM) methods. Among several MADM techniques considered, taken from the literature, the work is then focused on the TOPSIS approach, which allows introducing some improvements aimed at reducing the computational burden needed to select the RAT to be employed. The enhanced method is called Dynamic-TOPSIS (D-TOPSIS). Finally, the numerical results, obtained through a large simulative campaign and aimed at comparing the performance and the running time of the D-TOPSIS, the TOPSIS, and the algorithms found in the literature, are reported and discussed.
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Sivashankar, N., R. Thanigaivelan, and K. G. Saravanan. "Electrochemical micromachining and parameter optimization on AZ31 alloy—ANN and TOPSIS techniques." Bulletin of the Chemical Society of Ethiopia 37, no. 5 (June 30, 2023): 1263–73. http://dx.doi.org/10.4314/bcse.v37i5.17.
Full textAbstract:
ABSTRACT. Electrochemical micromachining (ECM) is a nontraditional method used for machining operations in hard and light materials with fixed or varying parameters. In this study, magnesium AZ31 alloy was micro machined using two types of electrolyte supply systems, namely electrolyte flooding and minimum quantity electrolyte (MQE). Experimental investigations were performed using TOPSIS and artificial neural network (ANN) techniques with types of electrolyte supply system, electrolyte concentration (EC), duty cycle (%), and machining voltage (V) as the input parameters, and material removal rate (MRR) and over cut (OC) as the outputs. Single and multi-objective parameter optimization was performed using Taguchi, TOPSIS, and ANN techniques. The machined microholes were analyzed using scanning electron microscopy. According to the TOPSIS results, under optimal conditions, a high MRR value and minimum OC of 1.282 μm/s and 66 μm, respectively, were obtained. The results of TOPSIS were verified using the developed ANN architecture.
KEY WORDS: Magnesium, AZ31 alloy, Electrochemical micromachining, Optimization, TOPSIS, ANN
Bull. Chem. Soc. Ethiop. 2023, 37(5), 1263-1273.
DOI: https://dx.doi.org/10.4314/bcse.v37i5.17
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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.
Full textAbstract:
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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Bakrim, La Ode, Aris Susanto, and Omar Wahid. "Sistem Pendukung Keputusan Penilaian Widyaiswara Pendidikan dan Pelatihan CPNS Menggunakan Metode TOPSIS Pada BPSDM Sulawesi Tenggara." SIMKOM 5, no. 1 (January 31, 2020): 45–56. http://dx.doi.org/10.51717/simkom.v5i1.78.
Full textAbstract:
Penelitian ini bertujuan untuk mengembangkan sistem pendukung keputusan yang dapat mengevaluasi widyaiswara pelatihan CPNS pada BPSDM Provinsi Sulawesi Tenggara. Metode pengumpulan data yang digunakan dalam penelitian ini yaitu studi literatur, observasi, dan kuisioner. Sedangkan metode analisis data yang digunakan yaitu algoritma TOPSIS dengan merangking setiap widyaiswara berdasarkan nilai preferensi yang diperoleh. Hasil pengujian akurasi metode TOPSIS dalam penelitian ini sangat rendah. Namun, berdasarkan alternatif keputusan yang direkomendasikan TOPSIS memiliki kesesuaian dengan alternatif yang direkomendasikan secara konvensional.
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Dewi, Ratih Kartika, Mahardeka Tri Ananta, Lutfi Fanani, Komang Candra Brata, and Nurizal Dwi Priandani. "The Development of Mobile Culinary Recommendation System Based on Group Decision Support System." International Journal of Interactive Mobile Technologies (iJIM) 12, no. 3 (July 20, 2018): 209. http://dx.doi.org/10.3991/ijim.v12i3.7799.
Full textAbstract:
Mobile based culinary recommendation system has received significant attention in recent mobile application research . Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) has regained popularity in supporting multi-criteria decision making due to this method allowing inclusion of many factors and criteria into the decision making process. Previous works on mobile based scenario culinary recommendation system reveal that TOPSIS stand out from other recommendation approaches like AHP and Fuzzy by providing a lightweight computation algorithm that have promising performance in time complexity. However, computing a culinary recommendation using TOPSIS has own limitations especially in the menu judgment processes due to the alternatives priority only include personal preferences for recommendation. In such a culinary recommendation system scenario, users more likely search culinary menus in group instead of alone. This research aims to develop a culinary recommendation system based on group decision support system (GDSS) using TOPSIS that possible to calculate a recommendation by using group preferences instead of personal preferences. The experimental results show that the overall functional of proposed GDSS gives better recommendation result. GDSS using TOPSIS have 100% rank consistency for 6 group of users with 5 combination of menus. The accuracy testing shows that 83,33 % recommendation of GDSS TOPSIS are match with real user preferences. Furthermore, it can be run well in various type of Android smartphone.