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Journal articles on the topic 'Fuzzy PROMETHEE'

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Published: 7 June 2025

Last updated: 16 July 2025

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Soni, Vivek, Surya Prakash Singh, and Devinder Kumar Banwet. "Precise decisions in Indian energy sector by imprecise evaluation." International Journal of Energy Sector Management 10, no. 1 (2016): 118–42. http://dx.doi.org/10.1108/ijesm-12-2014-0011.

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Purpose – The purpose of this paper is to prioritize Indian energy sector projects, namely, coal, gas, hydro and solar using fuzzy PROMETHHE (F-PROMETHEE) and Visual PROMETHEE applications and multicriteria decision-making (MCDM) analyses. Design/methodology/approach – The MCDM outranking approach of PROMETHEE under fuzzy environment is used. Four projects of energy sector are selected as alternatives and are compared based on various criteria. These criteria selected on the perspectives of life cycle costing (LCC) analysis and related management approaches for prioritizing projects for effective decision-making (DM). The F-PROMETHEE is described and results are also compared with outranking application in Visual PROMETHEE software based on same set of criteria. For better understanding, the graphical representations of the multicriteria problem are also shown using graphical analysis for interactive aid. Findings – On applying F-PROMETHEE on four energy projects, coal and solar projects outrank high and results shows that coal-based project is preferable and should be considered. Research limitations/implications – Here F-PROMETHEE and Visual PROMETHEE are used as MCDM techniques. However, few other MCDM techniques such as ELECTRE and EATWOS can be also explored to outrank Indian energy sector projects. Practical implications – Indian energy sector involves high degree of complexity for effective DM on the front of prioritized investment-related capacity addition through energy projects. Outranking methods like F-PROMETHEE is able to address the criteria to criteria impact on DM support precisely. Social implications – The finding can provide information to the government or public sector regarding various possible investment options on energy projects in India. Originality/value – This paper can be supplement and act as the support for DM in conflicting situations specifically for prioritizing investments on various energy projects, which further can synergize conflicting ideas of various stakeholders of the Indian energy sector.

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Akram, Muhammad, Shumaiza, and Ahmad N. Al-Kenani. "Multi-Criteria Group Decision-Making for Selection of Green Suppliers under Bipolar Fuzzy PROMETHEE Process." Symmetry 12, no. 1 (2020): 77. http://dx.doi.org/10.3390/sym12010077.

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The preference ranking organization method for enrichment of evaluations (PROMETHEE) method considers a significant outranking class of multi-criteria decision analysis (MCDA), as it is easy to deal with its simple computations. In the PROMETHEE, different preference functions are used according to the type and nature of attributes or criteria that demonstrate the clearness and reliability of this method. This study provides a new version of the PROMETHEE method using bipolar fuzzy information, named the bipolar fuzzy PROMETHEE method. Bipolar fuzzy sets or numbers constitute an asymmetrical relationship between two judgmental factors of human reasoning. Vague and imprecise knowledge is characterized by bipolar fuzzy linguistic terms which are further represented in the form of trapezoidal bipolar fuzzy numbers. The trapezoidal bipolar fuzzy numbers are used by analysts to assign the preferences of alternatives on the basis of criteria. Further, a ranking function of bipolar fuzzy numbers is considered to access the crisp real preferences of alternatives. The entropy weighting information is employed to calculate the weights of attributes by considering the condition of normality. A numerical example such as the selection of green suppliers by using the bipolar fuzzy PROMETHEE is performed on the basis of the usual criterion preference function in order to explain the procedure of the proposed method. Comparable results are derived by using the combination of linear and level preference functions. The results obtained by using different types of preference functions are the same, representing the authenticity of the proposed bipolar fuzzy PROMETHEE method.

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Akram, Muhammad, Maheen Sultan, José Carlos R. Alcantud, and Mohammed M. Ali Al-Shamiri. "Extended fuzzy $ N $-Soft PROMETHEE method and its application in robot butler selection." Mathematical Biosciences and Engineering 20, no. 2 (2023): 1774–800. http://dx.doi.org/10.3934/mbe.2023081.

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<abstract>This paper extends the literature on fuzzy PROMETHEE, a well-known multi-criteria group decision-making technique. The PROMETHEE technique ranks alternatives by specifying an allowable preference function that measures their deviations from other alternatives in the presence of conflicting criteria. Its ambiguous variation helps to make an appropriate decision or choose the best option in the presence of some ambiguity. Here, we focus on the more general uncertainty in human decision-making, as we allow $ N $-grading in fuzzy parametric descriptions. In this setting, we propose a suitable fuzzy $ N $-soft PROMETHEE technique. We recommend using an Analytic Hierarchy Process to test the feasibility of standard weights before application. Then the fuzzy $ N $-soft PROMETHEE method is explained. It ranks the alternatives after some steps summarized in a detailed flowchart. Furthermore, its practicality and feasibility are demonstrated through an application that selects the best robot housekeepers. The comparison between the fuzzy PROMETHEE method and the technique proposed in this work demonstrates the confidence and accuracy of the latter method.</abstract>

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Elevli, Birol. "LOGISTICS FREIGHT CENTER LOCATIONS DECISION BY USING FUZZY-PROMETHEE." TRANSPORT 29, no. 4 (2014): 412–18. http://dx.doi.org/10.3846/16484142.2014.983966.

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Fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (F-PROMETHEE) was applied for choosing among potential logistics center locations. The method combines the concept of fuzzy sets to represent uncertain information with the PROMETHEE, a subgroup of Multi-Criteria Decision-Making (MCDM) methods. Criteria are identified based on review of scientific and trade literature and inputs received from experts. The suitability of areas have been evaluated on the basis of these criteria. There are substantial uncertainties and subjectivity about site information. Therefore F-PROMETHEE method is preferred. The case study shows that this application provides reasonable results.

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Samanlioglu, Funda, and Zeki Ayağ. "An intelligent approach for the evaluation of transformers in a power distribution project." Journal of Intelligent & Fuzzy Systems 39, no. 3 (2020): 4133–45. http://dx.doi.org/10.3233/jifs-200261.

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In this study, a hybrid approach is presented for the evaluation and selection of transformers in a power distribution project. Ranking transformers and selecting the best among alternatives is a complex multiple criteria decision making (MCDM) problem with various possibly conflicting quantitative and qualitative criteria. In this research, two hesitant fuzzy MCDM methods; hesitant fuzzy Analytic Hierarchy Process (hesitant F-AHP) and hesitant fuzzy Preference Ranking Organization Method for Enriching Evaluations II (hesitant F-PROMETHEE II) are combined to evaluate and rank transformers. In the hesitant fuzzy AHP-PROMETHEE II, hesitant F-AHP is implemented to determine criteria weights and hesitant F-PROMETHEE II is applied to rank transformer alternatives, utilizing obtained criteria weights. An illustrative example is presented to demonstrate the effectiveness and applicability of the proposed approach. In the example, five transformers are evaluated based on twelve criteria by three decision makers (DMs) and best alternative is selected. For comparison analysis, integration of hesitant F-AHP and hesitant fuzzy Technique for Order Preference by Similarity to Ideal Solution (hesitant F-TOPSIS) is used and results are compared.

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Baki, Rahmi. "For Supplier Evaluation Process through Fuzzy PROMETHEE Method." International Journal of Materials, Mechanics and Manufacturing 5, no. 3 (2017): 183–86. http://dx.doi.org/10.18178/ijmmm.2017.5.3.314.

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Aruchsamy, Revathy, Inthumathi Velusamy, Krishnaprakash Sanmugavel, Prasantha Bharathi Dhandapani, and Kavikumar Ramasamy. "Generalization of Fermatean Fuzzy Set and Implementation of Fermatean Fuzzy PROMETHEE II Method for Decision Making via PROMETHEE GAIA." Axioms 13, no. 6 (2024): 408. http://dx.doi.org/10.3390/axioms13060408.

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The Fermatean fuzzy set, in contrast to other generalizations of fuzzy sets like PFS and IFS, has a wide range of acceptance for both MF and NMF. In light of this, the Fermatean fuzzy set performs as an efficient, flexible, and comprehensive representation in situations that lack certainty. Here, the weaker forms of Fermatean fuzzy sets are introduced, and their traits are analyzed. Decomposition and continuity of the Fermatean fuzzy α-open set are also accustomed. With the goal of safeguarding our green environment, hiring the best supplier is of the utmost significance in the construction industry. Using outranking techniques, Visual PROMETHEE Academic Edition 1.4 is a live multi-criteria decision aid software program. It runs virtual analysis through GAIA and applies selected criteria to contrast parameters. It also saves them for possible export and editing. In this article, the PROMETHEE II method is applied for Fermatean fuzzy numbers with FF(α,β)−level for selecting the optimal green supplier for a construction company. Because of its ability to handle vagueness, the FF PROMETHEE II method emerges as a valuable tool in Multi-criteria decision making. Furthermore, this study assesses the efficacy of the proposed technique by comparing its results with those obtained through other established methods.

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Agada, Alexander Iwodi, John Rajan, Swaminathan Jose, et al. "Integration of Fuzzy 0/1 Knapsack Dynamic Programming and PROMETHEE Method for Vehicle Exhaust Emission Parametric Optimization and Selection in the Packing Industry." International Journal of Industrial Engineering and Engineering Management 6, no. 2 (2024): 97–112. https://doi.org/10.24002/ijieem.v6i2.7689.

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Packaging industries fabricate and transport products in wrapped, sealed, and cushioned containers and boxes on roads, often through fossil-fuelled vehicles that emit carbons. Thus, decarbonization and net zero emission drive are compelling for these vehicles. This paper proposes a robust green logistics interaction model for monitoring and reducing exhaust pipe emissions in an uncertain environment. It uses a hybrid method known as fuzzy-0/1-KDP-PROMETHEE (Fuzzy-0/1 Knapsack dynamic programming-Preference Ranking Organization Method for Enrichment Evaluation) approach to concurrently reduce uncertainty, optimize the capacity of the knapsack and establish the preferred option among the parameters of green logistic. Both PROMETHEE I and II were introduced and tested using logistics data from an Indian environment based on secondary data. The method works by first reducing the effect of uncertainty on the model outcomes. This was achieved by establishing the output space as the fuzzy state, creating fuzzy rules, and mapping degrees to rules. Then, the degrees are used to maximize, ensuring that the weighted sum is not greater than the capacity of the Knapsack. The outcome is then regarded as the element of the green logistics exhaust emission process. The results obtained from the analysis, using the replacement of fuzzy expert (triangular) with fuzzy extent (trapezoidal), fuzzy geometric mean (triangular), and fuzzy geometric mean (trapezoidal) reveal that the fuzzy-0/1-KDP-PROMETHEE method adequately represents the score obtained using the data set from the exhaust emissions.

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Dubo, He, and Huang Dong. "Supply Chain Quality Performance Evaluation Model Based on Intuitionistic Fuzzy PROMETHEE." E3S Web of Conferences 214 (2020): 03036. http://dx.doi.org/10.1051/e3sconf/202021403036.

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Aiming at the ambiguity and uncertainty in subjective group decision-making of supply chain quality performance evaluation, the traditional preference ranking organization methods for enrichment evaluation (PROMETHEE) is extended to a fuzzy environment, and a new intuitive fuzzy PROMETHEE model is proposed. The model uses intuitionistic fuzzy numbers to express the decision-maker’s semantic evaluation information, and establishes a trust function based on the evaluation information to determine the decision-maker’s weight. Then, use the method of maximizing the net flow to obtain the attribute weight. Finally, gather the evaluation information to obtain the decision group’s pros and cons. The validity and feasibility of the model is verified by an example.

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Huzumah, Nur, and Toni Arifin. "Sistem Pemilihan Mesin Cuci Berdasarkan Kebutuhan Konsumen Menggunakan Fuzzy Tahani dan Promethee." Jurnal Informatika 5, no. 1 (2018): 12–21. http://dx.doi.org/10.31311/ji.v5i1.2728.

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Abstrak Berdasarkan hasil survei terhadap kebutuhan mesin cuci pada tahun 2013 pertumbuhan mesin cuci nasional naik sebesar 28%, Menurut data Euro Monitor tahun 2017, penetrasi mesin cuci di Indonesia selama lima tahun terakhir terus meningkat. Sekitar 74% masyarakat di Kota besar seperti Jakarta telah mengandalkan mesin cuci untuk membantu membersihkan pakaian. Namun pada pembelian mesin cuci, sebagian besar masyarakat masih tertarik dengan harga yang murah tanpa mengetahui spesifikasi detail mengenai mesin cuci yang akan dibeli apakah sesuai kebutuhan atau tidak. Karena kurangnya kesadaran masyarakat, maka dibuat sebuah sistem pendukung keputusan menggunakan metode fuzzy tahani dan promethee untuk meningkatkan kualitas rekomendasi mesin cuci sesuai kebutuhan konsumen. Metode fuzzy tahani digunakan untuk melakukan pengurutan data mesin cuci berdasarkan kriteria yang menghasilkan nilai 0 sampai dengan 1. Setelah itu, metode promethee digunakan untuk mendapatkan bobot mesin cuci dan akan dilakukan pengurutan mesin cuci sesuai bobot yang didapat. Hasil penelitian ini menunjukkan bahwa adanya sistem pendukung keputusan yang dibangun, masyarakat yang ingin membeli mesin cuci dapat memilih dengan tepat, jelas dan objektif. Hasil akurasi yang dihasilkan adalah 90%.  Kata Kunci: sistem pendukung keputusan, pemilihan mesin cuci, fuzzy tahani, promethee  Abstract Based on results of survey about the needs of washing machines in 2013, the growth of national washing machines increased by 28%. According to Euro Monitor Data of 2017, penetration of washing machines in Indonesia over the last five years continues to increase. About 74 % of the people in big cities like Jakarta have relied on a washing machine to help clean clothes. However on the purchase of a washing machine, most of the people still interested in a cheap price without knowing detail specification of the washing machine which will be purchased whether as needed or not. Due the lack of public awareness, then made a decision support system using fuzzy tahani and promethee method to improve the quality of the washing machine recommendations according to needs of the consumers. Fuzzy tahani method is used to perform the washing machine data sorting based on the cirteria that yields a value of 0 to 1. After that, Promethee method is used to get weight of the washing machine and will do sorting machine according to the weight obtained. The results of this study indicate that a decision support system who has been built, people who want to buy a washing machine can choose the washing machine properly, cleary and objectively. The result of accuracy is 90%.  Keywords: decision support system, washing machine selection, fuzzy tahani, promethee

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Bashir, Muhammad Adnan, Tabasam Rashid, and Muhammad Salman Bashir. "Generalized Ordered Intuitionistic Fuzzy C-Means Clustering Algorithm Based on PROMETHEE and Intuitionistic Fuzzy C-Means." International Journal of Intelligent Systems 2023 (September 22, 2023): 1–21. http://dx.doi.org/10.1155/2023/6686446.

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The problem of ordered clustering in the context of decision-making with multiple criteria has garnered significant interest from researchers in the field of management science and operational research. In real-world scenarios, the datasets often exhibit imprecision or uncertainty, which can lead to suboptimal ordered-clustering outcomes. However, the intuitionistic fuzzy c-means (IFCM) clustering algorithm enhances the accuracy and effectiveness of decision-making processes by effectively handling uncertain dataset information for clustering. Therefore, we propose a new clustering algorithm, called the generalized ordered intuitionistic fuzzy c-means (G-OIFCM), based on PROMETHEE and the IFCM clustering algorithm. Different from the classical IFCM clustering algorithm, we use positive flow ( φ + s i ∈ 0 , 1 ) and negative flow ( φ − s i ∈ 0 , 1 ) of PROMETHEE to generate ordered clusters within the intuitionistic environment. We define a new objective function based on the positive and negative flow of the PROMETHEE and IFCM clustering algorithm, whose properties are mathematically justified in terms of convergence and optimization. The performance of the proposed algorithm is evaluated using two different real-world datasets to assess both the ordered clustering and the quality of partitioning. To demonstrate the effectiveness of G-OIFCM, a comparison is conducted with three other algorithms: fuzzy c-means (FCM), ordered fuzzy c-means (OFCM), and an adaptive generalized intuitionistic fuzzy c-means (G-IFCM). The results demonstrate the effectiveness of G-OIFCM in enhancing optimal ordered clustering and utility when dealing with uncertainty in datasets.

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Mahmoudi, Amin, Soheil Sadi-Nezhad, Ahmad Makui, and Mohammad Reza Vakili. "An extension on PROMETHEE based on the typical hesitant fuzzy sets to solve multi-attribute decision-making problem." Kybernetes 45, no. 8 (2016): 1213–31. http://dx.doi.org/10.1108/k-10-2015-0271.

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Purpose The purpose of this paper is to extend the PROMETHEE method under typical hesitant fuzzy information for solving multi-attribute decision-making problem in which there is hesitancy among experts. Design/methodology/approach Different aggregation and distance functions were developed to deal with HFS. But it is rational that different operators applying in existing methods can produce different results. Also, it is difficult for decision makers to select suitable operators. To address the drawback, this paper develops the PROMETHEE method as an outranking approach to accommodate hesitant fuzzy information. Since the proposed method is constructed on the basis of the pair-wise comparisons, it is independent of the aggregation and distance functions. Findings To demonstrate the efficiency and accuracy of the proposed method, the authors provide a numerical example and a comparative analysis. The results indicate that outranking-based methods suggest a better ranking than the aggregation- and distance-based methods. Research limitations/implications The proposed approach does not consider the hesitant fuzzy linguistic information decision-making problem. Practical implications The proposed approach can be applied in many group decision-making problems in which there is hesitancy among experts. Originality/value This paper proposes an extension on PROMETHEE method under hesitant fuzzy information, which has not been reported in the existing academic literature.

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Priya,, M., and R. Kumaravel,. "Exploring Water Quality Assessment through AHP and Picture Fuzzy PROMETHEE - II: An In-Depth Investigation." Malaysian Journal of Mathematical Sciences 18, no. 3 (2024): 515–27. http://dx.doi.org/10.47836/mjms.18.3.04.

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Effective analysis of water quality is crucial for the well-being of ecosystems and human populations, notably in rivers like Thirumanimutharu. This study advances current methodologies by integrating the picture fuzzy PROMETHEE II approach with the analytic hierarchy process (AHP), offering a robust solution to the challenges posed by data ambiguity and imprecision. Born from the fusion of PROMETHEE II with picture fuzzy sets, this innovative method adeptly represents qualitative criteria and linguistic notions inherent in water quality assessment. A practical case study, utilising real water quality data, demonstrates the superior accuracy and durability of the combined picture fuzzy PROMETHEE II and AHP approach compared to traditional methods. These results significantly contribute to our understanding of water quality assessment, providing essential insights for environmental experts and decision-makers. The approach�s efficacy is particularly highlighted in the management and conservation of water resources in the Thirumanimutharu river, emphasising the need for advanced methodologies in environmental conservation and resource management. This research underscores the importance of adopting sophisticated techniques for more informed decision-making, ultimately contributing to the water resources and the preservation of ecological balance in the Thirumanimutharu river and similar water bodies.

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Ozsahin, Ilker. "Identifying a Personalized Anesthetic with Fuzzy PROMETHEE." Healthcare Informatics Research 26, no. 3 (2020): 201–11. http://dx.doi.org/10.4258/hir.2020.26.3.201.

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Vavatsikos, A. P., O. E. Demesouka, and K. P. Anagnostopoulos. "GIS-based suitability analysis using fuzzy PROMETHEE." Journal of Environmental Planning and Management 63, no. 4 (2019): 604–28. http://dx.doi.org/10.1080/09640568.2019.1599830.

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Fernández-Castro, A. S., and M. Jiménez. "PROMETHEE: an extension through fuzzy mathematical programming." Journal of the Operational Research Society 56, no. 1 (2005): 119–22. http://dx.doi.org/10.1057/palgrave.jors.2601828.

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Akram, Muhammad, Shumaiza, and José Alcantud. "An m-Polar Fuzzy PROMETHEE Approach for AHP-Assisted Group Decision-Making." Mathematical and Computational Applications 25, no. 2 (2020): 26. http://dx.doi.org/10.3390/mca25020026.

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The Analytical Hierarchy Process (AHP) is arguably the most popular and factual approach for computing the weights of attributes in the multi-attribute decision-making environment. The Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE) is an outranking family of multi-criteria decision-making techniques for evaluating a finite set of alternatives, that relies on multiple and inconsistent criteria. One of its main advantages is the variety of admissible preference functions that can measure the differences between alternatives, in response to the type and nature of the criteria. This research article studies a version of the PROMETHEE technique that encompasses multipolar assessments of the performance of each alternative (relative to the relevant criteria). As is standard practice, first we resort to the AHP technique in order to quantify the normalized weights of the attributes by the pairwise comparison of criteria. Afterwards the m-polar fuzzy PROMETHEE approach is used to rank the alternatives on the basis of conflicting criteria. Six types of generalized criteria preference functions are used to measure the differences or deviations of every pair of alternatives. A partial ranking of alternatives arises by computing the positive and negative outranking flows of alternatives, which is known as PROMETHEE I. Furthermore, a complete ranking of alternatives is achieved by the inspection of the net flow of alternatives, and this is known as PROMETHEE II. Two comparative analysis are performed. A first study checks the impact of different types of preference functions. It considers the usual criterion preference function for all criteria. In addition, we compare the technique that we develop with existing multi-attribute decision-making methods.

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Narayanamoorthy, Samayan, Subramaniam Pragathi, Thirumalai Nallasivan Parthasarathy, et al. "The COVID-19 Vaccine Preference for Youngsters Using PROMETHEE-II in the IFSS Environment." Symmetry 13, no. 6 (2021): 1030. http://dx.doi.org/10.3390/sym13061030.

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Extensive decision-making during the vaccine preparation period is unpredictable. An account of the severity of the disease, the younger people with COVID-19 comorbidities and other chronic diseases are also at a higher risk of the COVID-19 pandemic. In this research article, the preference ranking structure for the COVID-19 vaccine is recommended for young people who have been exposed to the effects of certain chronic diseases. Multiple Criteria Decision-Making (MCDM) approach effectively handles this vague information. Furthermore, with the support of the Intuitionistic Fuzzy Soft Set (IFSS), the entries under the new extension of the Preference Ranking Organization Method for Enrichment Evaluation-II (PROMETHEE-II) is suggested for Preference Ranking Structure. The concept of intuitionistic fuzzy soft sets is parametric in nature. IFSS suggests how to exploit an intuitionistic ambiguous input from a decision-maker to make up for any shortcomings in the information provided by the decider. The weight of the inputs is calculated under the Intuitionistic Fuzzy Weighted Average (IFWA) operator, the Simply Weighted Intuitionistic Fuzzy Average (SWIFA) operator, and the Simply Intuitionistic Fuzzy Average (SIFA) operator. An Extended PROMETHEE-based ranking, outranking approach is used, and the resultant are recommended under the lexicographic order. Its sustainability and feasibility are explored for three distinct priority structures and the possibilities of the approach. To demonstrate the all-encompassing intuitionistic fuzzy PROMETHEE approach, a practical application regarding COVID-19 severity in patients is given, and then it is compared to other existing approaches to further explain its feasibility, and the sensitivity of the preference structure is examined according to the criteria.

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Sarwar, Musavarah, Fariha Zafar, Iqra Abdul Majeed, and Soha Javed. "Selection of Suppliers in Industrial Manufacturing: A Fuzzy Rough PROMETHEE Approach." Mathematical Problems in Engineering 2022 (July 8, 2022): 1–19. http://dx.doi.org/10.1155/2022/6141225.

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In supply chain management (SCM), the selection of suppliers plays a vital role in an efficient production process. Over the last few years, to form a trade-off between the quantitative and qualitative criteria, the selection of suppliers in SCM is considered very conclusive. The decisions generally demand different criteria to balance between every possible inconsistent parameters involving subjectivity and uncertainty in the process. The evaluation information mostly depends on the experience and knowledge of experts that are unsure and indistinct. This study introduces a novel decision-making method by integrating rough approximations with fuzzy numbers and preference ranking organization method for enrichment evaluation (PROMETHEE) to deal with subjective and objective vagueness in the assessment of decision makers. To minimize the dependency on experts’ judgements, entropy weights are computed from the original data set. The preference index is then computed using entropy weights and deviations among alternatives. The alternatives are ranked using the intersection of both positive flow and negative flow. To show the significance and importance of fuzzy rough PROMETHEE method, a case study of supplier selection in industrial manufacturing is discussed in detail. The developed method is effectively used to rank the supplier alternatives under given criteria. The results are then compared with different rough numbers and fuzzy numbers based on MCDM methods. The fuzzy rough PROMETHEE method can be efficiently used for the selection of the best suppliers to reduce losses and maximize the production process.

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Kumari, Archana, Deepa Kumari, and Reema Agarwal. "Evaluating Mobile Wallet Adoption Barriers Using Fuzzy Mathematical Model." International Journal of Experimental Research and Review 44 (October 30, 2024): 266–76. http://dx.doi.org/10.52756/ijerr.2024.v44spl.023.

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A tremendous amount of research has been done on the factors influencing mobile wallet adoption as mobile wallet technology has seen rapid growth. Using expert opinion and Fuzzy PROMETHEE approach, this study investigates the key barriers to mobile wallet adoption. Mobile wallet adoption is constrained by Technological, security and infrastructural barriers, making adoption more challenging when user acceptance is skewed in emerging markets. In this study, we use the F-PROMETHEE to rank these barriers based on expert opinions. A panel of fintech and digital payments experts assessed the key adoption obstacles. Included in the PROMETHEE method were methods for handling variability or uncertainty through fuzzy logic and through subjective expert judgments. The results suggest that the major barriers to the adoption of mobile wallets were identified as risk and usage constraints. Moreover, value barriers are a leading factor. This study found that the risk and value barriers are the two principal risks that must be overcome to raise the client accepted rate of m-wallet services. A step forward in the assessment of such obstacles is the innovative use of a fuzzy mathematical model, which provides a more complex and adaptable approach than traditional methods. This study has learnt a few lessons that can help policy makers and industry players understand how to overcome the main barriers to mobile wallet adoption.

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Citil, Mehmet. "An application of the intuitionistic fuzzy PROMETHEE method in the selection of transportation service." Thermal Science 26, Spec. issue 2 (2022): 613–20. http://dx.doi.org/10.2298/tsci22s2613c.

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Many of the problems we encounter involve uncertainties. Intuitionistic fuzzy logic works well in solving problems with uncertainties. Transportation problems, which are needed find the most appropriate and best, also contain uncertainty. A solution is found by using one of the decision making methods by determining the weight values of the criteria. The PROMETHEE method has an important place among the multi-criteria decision-making methods as it allows the decision maker to observe both positive and negative rankings. We may solve problems with uncertainties through using intuitionistic fuzzy logic. In this study, a new and different solution method is presented to find the most suitable transportation service provider by using the intuitionistic fuzzy PROMETHEE method. Criterion weight values were determined by controlled sets. Decision makers may apply this method to their problems by changing the weights we use depending on the importance of their criteria.

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Nguyen, Huyen Trang, and Ta-Chung Chu. "Ranking Startups Using DEMATEL-ANP-Based Fuzzy PROMETHEE II." Axioms 12, no. 6 (2023): 528. http://dx.doi.org/10.3390/axioms12060528.

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In entrepreneurship management, the evaluation and selection of startups for acceleration programs, especially technology-based startups, are crucial. This process involves considering numerical and qualitative criteria such as sales, prior startup experience, demand validation, and product maturity. To effectively rank startups based on the varying importance of these criteria, a fuzzy multi-criteria decision-making (MCDM) approach is needed. Although MCDM methods have been successful in handling complex problems, their application in startup selection and evaluating criteria interrelationships from the accelerator perspective is underexplored. To address this gap, a hybrid DEMATEL-ANP-based fuzzy PROMETHEE II model is proposed in this study, facilitating startup ranking and examining interrelationships among factors. The resulting preference values are fuzzy numbers, necessitating a fuzzy ranking method for decision-making. An extension of ranking fuzzy numbers using a spread area-based relative maximizing and minimizing set is suggested to enhance the flexibility of existing ranking MCDM methods. Algorithms, formulas, and a comparative analysis validate the proposed method, while a numerical experiment verifies the viability of the hybrid model. The final ranking of four startup projects is A4<A1<A3<A2 which indicates that startup project A2 has the highest comprehensive potential, followed by startup project A3.

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Akram, Muhammad, Maheen Sultan, Arooj Adeel, and Mohammed M. Ali Al-Shamiri. "Pythagorean fuzzy $ N $-Soft PROMETHEE approach: A new framework for group decision making." AIMS Mathematics 8, no. 8 (2023): 17354–80. http://dx.doi.org/10.3934/math.2023887.

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<abstract>The use of Pythagorean fuzzy $ N $-soft sets (PFNSs) enables the examination of belongingness and non-belongingness of membership degrees, as well as their combinations with $ N $-grading, in the unpredictable nature of individuals. This research aims to enhance our understanding of a popular multi-criteria group decision making (MCGDM) technique, Preference Ranking Organization Method for Enrichment of Evaluations, under the PFNS environment, aiding in making effective decisions for real-life problems, as fuzzy set theory is directly relevant to real-life applications. The PROMETHEE technique's main principle is to calculate the inflow and outflow streams of alternatives based on the deviation of their score degrees, ultimately providing partial and complete rankings of the given options. To capture the uncertainty of human nature, which demands both the association and disassociation of the considered criteria and provision of $ N $-grading, the PFNS PROMETHEE technique is introduced in this research article. First, an Analytic Hierarchy Process AHP is used to check the feasibility of the standard weights of the criteria. The article then explains the detailed method of the fuzzy $ N $-soft PROMETHEE technique to rank alternatives, with all the steps presented in an extensive flowchart for better understanding of the methodology. Furthermore, the practicality and viability of the proposed technique are demonstrated through an example of selecting the best chemical element in cloud seeding, where the most suitable choice is identified using an outranking directed graph. The credibility of the PFNS PROMETHEE technique is assessed by comparison with an existing method. Finally, the proposed technique's strengths and weaknesses are discussed to demonstrate its efficiency and drawbacks.</abstract>

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He, Tianhong, and Qingmao Wang. "Analyzing the Service Quality Evaluation of Railway Cold Chain Logistics Based on Probabilistic Linguistic Group Decision-Making." International Journal of Decision Support System Technology 17, no. 1 (2025): 1–20. https://doi.org/10.4018/ijdsst.371200.

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The evaluation of railway cold chain logistics service quality is essential for ensuring the safe, efficient, and reliable transport of temperature-sensitive goods, such as food and pharmaceuticals. It identifies strengths and weaknesses in logistics processes, enabling continuous improvement and optimal resource allocation. As the evaluation of railway cold chain logistics involves multiple-attribute group decision-making (MAGDM), this study employs the TODIM and PROMETHEE approaches to propose a robust framework. To effectively manage fuzzy information during the quality evaluation process, probabilistic linguistic term sets (PLTSs) are utilized. The study manages the probabilistic linguistic TODIM-PROMETHEE (PL-TODIM-PROMETHEE) approach, which is specifically designed to address MAGDM problems within the PLTSs framework. To determine weight values in this context, the MEREC approach is applied. Finally, a numerical example evaluating the service quality of railway cold chain logistics is provided to validate the effectiveness of the PL-TODIM-PROMETHEE approach.

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Tian, Xiaoli, Zeshui Xu, and Jing Gu. "GROUP DECISION-MAKING MODELS FOR VENTURE CAPITALISTS: THE PROMETHEE WITH HESITANT FUZZY LINGUISTIC INFORMATION." Technological and Economic Development of Economy 25, no. 5 (2019): 743–73. http://dx.doi.org/10.3846/tede.2019.8741.

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Venture capitalists (VCs) have long been preoccupied by the issue of selecting a promising start-up firm, whereas, ranking the available start-up firms is an effective way to solve this issue. In this paper, the PROMETHEE is chosen to be the fundamental ranking method. Also, the hesitant fuzzy linguistic term set is a suitable tool to simulate VCs’ evaluation information. Additionally, as the deepening of social division of labor and specialization of individuals, group decision making is famous for improving decision-making quality. Moreover, in the decision-making process, VCs exhibit behavioral characteristics which is depicted well by prospect theory that VCs are risk averse for gains and risk seeking for losses and rely on the transformed probability to make their decisions rather than unidimensional probability. Thus, a group prospect PROMETHEE with hesitant fuzzy linguistic information is constructed for VCs to make a better decision. Then, the proposed method is applied to rank start-up firms and the comparative analyses are made as well. It confirms that the group prospect PROMETHEE is better in describing the common behavioral characteristics of VCs and in enhancing the quality of evaluation.

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Samanlioglu, Funda, and Zeki Ayağ. "Concept selection with hesitant fuzzy ANP-PROMETHEE II." Journal of Industrial and Production Engineering 38, no. 7 (2021): 547–60. http://dx.doi.org/10.1080/21681015.2021.1944918.

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Liao, Huchang, and Zeshui Xu. "Multi-criteria decision making with intuitionistic fuzzy PROMETHEE." Journal of Intelligent & Fuzzy Systems 27, no. 4 (2014): 1703–17. http://dx.doi.org/10.3233/ifs-141137.

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Nugroho, Yunanto Adi, Yu Sekiguchi, and Elia Oey. "Export Country Selection with Fuzzy AHP and PROMETHEE." International Journal of Business Excellence 1, no. 1 (2019): 1. http://dx.doi.org/10.1504/ijbex.2019.10021856.

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Feng, Feng, Zeshui Xu, Hamido Fujita, and Meiqi Liang. "Enhancing PROMETHEE method with intuitionistic fuzzy soft sets." International Journal of Intelligent Systems 35, no. 7 (2020): 1071–104. http://dx.doi.org/10.1002/int.22235.

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Erkeç, Tuncay Yunus, Fahri Alp Erdoğan, Salih Aygün, and Murat Sağbaş. "UAV Selection Using Fuzzy AHP and PROMETHEE Method." Journal of Aviation 9, no. 1 (2025): 13–18. https://doi.org/10.30518/jav.1545474.

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UAV (Unmanned Aerial Vehicle) is an aircraft that can fly by remote control or automated system and does not have the capacity to carry people. The optimal selection of UAVs is critical for the successful conduct of operations and the prevention of loss of life and property. The aim of this study is to prioritize the criteria affecting the selection of UAVs and to rank the Strategic UAVs based on these criteria. Thus, it is aimed to improve the UAV selection process of decision makers. As a result of the literature search, there were no studies on the most important criteria affecting the selection of operational, tactical and strategic UAVs. Therefore, Fuzzy AHP and PROMETHEE methods were applied to fulfill these objectives. As a result, it was determined that the most important criteria in the selection of UAVs are realizability, flight stability and payload success rate value.

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Abdullah, Lazim, Nurhatika Harun, Shalela Mohd Mahali, Naeem Jan, and Ewa Rak. "Preorder of Factors Affecting Oil Prices: Fuzzy PROMETHEE Approach." Journal of Mathematics 2022 (June 17, 2022): 1–15. http://dx.doi.org/10.1155/2022/2766945.

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Oil is a highly demanded worldwide product as oil prices can have a major economic and social impact. There are many factors affecting oil prices, but little is known about which factor mostly influenced oil prices. To understand what caused the fluctuation of oil prices, the investigation leading up to the identification of the factors must be constructed. Thus, this paper attempts to explore the factors that might have contributed to oil prices and analyze them using the fuzzy preference ranking organization method for enrichment evaluation (PROMETHEE) method. In particular, the objective of this study is to rank the influential factors affecting oil prices with the consideration of a few criteria. The fuzzy PROMETHEE model comprises four criteria and five factors as the input information. A group of four experts are invited to provide an evaluation on scales of 1 to 5 of the importance of factors with respect to criteria. In computation, the evaluations are treated as triangular fuzzy numbers in which the uncertainty in data is dealt with amicably. This approach combines the advantages of transformation equation and nonarithmetic mean of the defuzzification method that transforms triangular fuzzy numbers into crisp numbers. The results indicate that “supply and demand” is the most influential factor in determining oil prices. Comparative analysis and future research directions are also discussed at the end of this paper.

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Ayadi, Hana, Nadia Hamani, Lyes Kermad, and Mounir Benaissa. "Novel Fuzzy Composite Indicators for Locating a Logistics Platform under Sustainability Perspectives." Sustainability 13, no. 7 (2021): 3891. http://dx.doi.org/10.3390/su13073891.

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The purpose of this paper is to help decision-makers choose the location of a logistics platform with sustainability perspectives. This study presents a compensatory and partially compensatory approach to build composite indicators, using mainly fuzzy multi-criteria decision-making methods. In the first instance, the fuzzy full consistency method (F-FUCOM) was used to calculate the weight of the criteria and sub-criteria. In the second instance, two aggregation methods, namely the fuzzy multi-attribute ideal-real comparative analysis (F-MAIRCA) and the fuzzy preference ranking organization method for enrichment evaluation (F-PROMETHEE), were used to rank the location of a logistics platform. The novelty of the work lays in studying the impact of limited sustainability and weak sustainability on the location of a logistics platform. In this respect, the aggregation of various sustainability criterion in fuzzy compensatory and partially compensatory composite indicators is an innovative and interesting approach used to locate a logistics platform. The obtained results show that economic sustainability is the most important criterion for the selection of a logistics platform, followed by the environmental criterion. Obviously, the F-MAIRCA and F-PROMETHEE methods provided the same ranking orders. Finally, sensitivity analyses were performed to validate the robustness of the proposed approach.

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Tian, Chao, Juan-juan Peng, Wen-yu Zhang, Shuai Zhang, and Jian-qiang Wang. "TOURISM ENVIRONMENTAL IMPACT ASSESSMENT BASED ON IMPROVED AHP AND PICTURE FUZZY PROMETHEE II METHODS." Technological and Economic Development of Economy 26, no. 2 (2019): 355–78. http://dx.doi.org/10.3846/tede.2019.11413.

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With the increasing awareness of environmental protection, the environmental impact assessment (EIA) of tourism attraction problems has attracted extensive attention from all over the world. The purpose of this study is to develop an integrated decision-making method for EIA of tourism attractions in China by using the improved analytic hierarchy process (AHP) method and the extended picture fuzzy preference ranking organization method for enrichment evaluations (PROMETHEE) II method. Herein, picture fuzzy numbers (PFNs) are used to describe decisionmakers’ preference, which can precisely express uncertain and hesitant information in the decisionmaking process. Then the improved AHP method based on expert mean assessment is used to obtain the weights of EIA of tourism attractions, which can reduce the spiteful assessment in the traditional AHP method. Based on the results of the improved AHP method, the picture fuzzy PROMETHEE II method, which can consider the psychological behavior of decision-makers, is applied to assess candidate tourism attractions. Finally, an example of EIA of tourism attractions in China is provided to verify the effectiveness of the developed approach and the credibility of the results.

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Mazaheri-Zadeh, Yoones, and Zahra Naji-Azimi. "Identification and Evaluation of Parameters Influencing the selection of Finance Project Contractors of Mashhad Water and Wastewater Company Using an AHP and Fuzzy Pramty." Current World Environment 10, Special-Issue1 (2015): 184–92. http://dx.doi.org/10.12944/cwe.10.special-issue1.24.

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For managers and decision-makers, selecting the contractor is a key decision given this fact that the contractor plays a fundamental role in any outsourced project. So, identifying and evaluating the contractors selection criteria will result in eliminating inefficient contractors from the tender process. It is needed to collect and process these criteria in order to maximize the performance of selected contractors, and to minimize the errors and mistakes in fulfilling the society needs and organization standards. Obviously, many quantitative and qualitative indicators of different importance are involved in determining the contractors' eligibility. In this paper, we are to identify the factors affecting the selection of contractors, and then, to determine the importance levels of the factors and prioritize the contractors by combining the multi-criteria methods of fuzzy AHP and fuzzy PROMETHEE. This is the first time to implement this hybrid method for solving the contractor selection problem. In this regard, first, the criteria are identified and their weights are calculated using the fuzzy AHP technique, then premier contractor is selected using the fuzzy PROMETHEE method. A real application to select finance projects' contractor in the Water and Wastewater Company of Mashhad city is considered as the base problem.

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Radeva, Irina. "Multicriteria Fuzzy Sets Application in Economic Clustering Problems." Cybernetics and Information Technologies 17, no. 3 (2017): 29–46. http://dx.doi.org/10.1515/cait-2017-0028.

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Abstract This paper presents an approach for small and medium-sized enterprises selection in economic clusters, where the problem of integration is defined as “ill structured under condition of uncertainty”. The proposed solution demonstrates applying several fuzzy multi-criteria decision making algorithms along with discussion over specific input data requirements. The results are compared with classical multi-criteria decision-making algorithm PROMETHEE II.

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Mohd Nasir, Diana Sirmayunie, Nurshahira Zawawi, and Suzanawati Abu Hasan. "Evaluate and Rank the Smartphone Brand Using Fuzzy AHP and PROMETHEE." Jurnal Intelek 14, no. 2 (2019): 44–51. http://dx.doi.org/10.24191/ji.v14i2.216.

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A buying decision process is one of the Multi-Criteria Decision Making (MCDM) problems faced by everyone in daily life. One example is the selection of smartphones brand in the market. Thus, the study is conducted to evaluate the most effective criteria for buying smartphones and to rank the people's preferences on smartphone based on its brand. Six criteria (price, operating system, memory, display, camera and battery) and three alternatives which are the smartphone brands (Oppo, Samsung and Apple) were chosen in the study. Two main processes were involved, which are 1) evaluate the smartphone criteria using Fuzzy Analytic Hierarchy Process (AHP) and 2) ranking the brand using Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE). Surveys and questionnaires were conducted and evaluated by decision makers who are the smartphone's users. The result showed storage memory is considered as prominent criteria in choosing a smartphone meanwhile the consumers firstly prefer Oppo, secondly Apple and thirdly Samsung. Future work in this study may use other alternatives to be ranked by considering other top models as well. Keywords: Multiple criteria decision making, smartphone brand, Fuzzy AHP, Fuzzy PROMETHEE

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Hamzeh, Mohamad, and Farid Karimipour. "Petroleum potential assessment using an optimized fuzzy outranking approach: A case study of the Red River petroleum system, Williston Basin." Energy Exploration & Exploitation 38, no. 4 (2020): 960–88. http://dx.doi.org/10.1177/0144598720910264.

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This paper presents a new approach, called optimized fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), based on combining fuzzy logic, an outranking method and the cuckoo search optimization algorithm to assess petroleum potential in a spatial framework. The approach brings together flexibility and simplicity to solve petroleum exploration problem under uncertainty using experts’ knowledge and the information associated with the discovered oil pools simultaneously. The characteristics of the essential elements of the petroleum system are used as key criteria in the model. To exemplify the approach, a case study was undertaken in the Red River petroleum system of the Canadian portion of the Williston Basin. Eight datasets related to the selected criteria were integrated by the optimized fuzzy PROMETHEE to create a map that makes it possible to identify the areas of highest petroleum potential. All discovered oil pools in the Red River petroleum system were used in the verification process. The results indicated that the proposed approach can deal effectively with incomplete data and imprecise information, and can be efficiently used in petroleum exploration, thereby reducing the cost and risk of exploration.

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Kamalkhani, Mahboubeh, Reza Sheikh, and Shib Sankar Sana. "Green performance evaluation and ranking hotels using fuzzy PROMETHEE." International Journal of Logistics Systems and Management 40, no. 4 (2021): 561. http://dx.doi.org/10.1504/ijlsm.2021.120493.

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Adhiana, Tigar Putri, Maria Krisnawati, and Hasyim Asyari. "Evaluasi Kinerja Pemasok Bahan Baku Menggunakan Metode Fuzzy Promethee." Dinamika Rekayasa 15, no. 2 (2019): 107. http://dx.doi.org/10.20884/1.dr.2019.15.2.271.

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Peran Industri Kecil Menengah (IKM) sangat penting untuk memasarkan produk atau layanan lokal ke pasar internasional serta bersaing dengan perusahaan pesaing multinasional di pasar lokal. Go Work Handy Craft adalah sebuah IKM yang memproduksi beberapa jenis sapu di Purbalingga. Permasalahan yang dihadapi Go Work Handy Craft adalah adanya keterlambatan pasokan bahan baku bambu dari pemasok. Apabila terjadi keterlambatan pasokan bahan baku bambu, maka proses produksi dihentikan sementara sehingga mengakibatkan produktivitas berkurang. Penelitian ini bertujuan untuk menilai kinerja pemasok secara keseluruhan dengan menggunakan kriteria kinerja. Metode yang digunakan adalah Fuzzy Promethee untuk mengevaluasi kinerja pemasok bahan baku pada IKM. Dari wawancara dan pengolahan data diperoleh bahwa Go Work Handy Craft memiliki 4 (empat) pemasok bahan baku bambu. Kriteria penilaian kinerja yang diperoleh melalui wawancara oleh pemilik IKM adalah harga yang kompetitif, ketersediaan barang, kualitas barang, lama waktu pengiriman dan kapasitas pengiriman. Dari pengolahan data diperoleh bahwa kinerja pemasok 2 yang paling baik dari pemasok lainnya dengan nilai Promethee II terbesar yaitu 0,0203.

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Sana, Shib, Mahboubeh Kamalkhani, and Reza Sheikh. "Green performance evaluation and ranking hotels using Fuzzy Promethee." International Journal of Logistics Systems and Management 1, no. 1 (2020): 1. http://dx.doi.org/10.1504/ijlsm.2020.10029755.

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Ozsahin, Dilber Uzun, Berna Uzun, Musa Sani Musa, Niyazi Şentürk, Fatih Veysel Nurçin, and Ilker Ozsahin. "Evaluating nuclear medicine imaging devices using fuzzy PROMETHEE method." Procedia Computer Science 120 (2017): 699–705. http://dx.doi.org/10.1016/j.procs.2017.11.298.

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Hosseini Motlagh, Seyyed Mahdi, Majid Behzadian, Joshua Ignatius, Mark Goh, Mohammad Mehdi Sepehri, and Tan Kim Hua. "Fuzzy PROMETHEE GDSS for technical requirements ranking in HOQ." International Journal of Advanced Manufacturing Technology 76, no. 9-12 (2014): 1993–2002. http://dx.doi.org/10.1007/s00170-014-6233-5.

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Chen, Ying-Hsiu, Tien-Chin Wang, and Chao-Yen Wu. "Strategic decisions using the fuzzy PROMETHEE for IS outsourcing." Expert Systems with Applications 38, no. 10 (2011): 13216–22. http://dx.doi.org/10.1016/j.eswa.2011.04.137.

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Ozsahin, I., B. Uzun, and D. U. Ozsahin. "Selection of photodetectors in nuclear medical imaging using MCDM methods." Journal of Instrumentation 17, no. 06 (2022): C06003. http://dx.doi.org/10.1088/1748-0221/17/06/c06003.

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Abstract Photodetectors used in nuclear medical imaging such as single photon emission computed tomography (SPECT) and positron emission tomography (PET) are an important element of radiation detection systems. Selecting the photodetector depends on many physical criteria including quantum efficiency (QE) and gain. The aim of this study is to apply multi-criteria decision-making (MCDM) methods to determine the optimum photodetector based on the evaluation and comparison of complex and multiple criteria. The photodetectors investigated in this study are photomultiplier tube (PMT), avalanche photodiode (APD) and silicon photomultiplier (SiPM). The bias voltage, gain, rise time, and QE were selected since they are considered as the key criteria for the photodetectors. Then, the corresponding values of each criteria were defined and preferred weights were assigned to each criteria based on the desired outcome. The fuzzy preference ranking organization method for enrichment of evaluations (PROMETHEE) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) methods were used to evaluate the alternatives. The results showed that conventional PMT came first in the ranking, followed by SiPM, while APD was the least desirable photodetector according to the fuzzy PROMETHEE and fuzzy TOPSIS methods based on the selected criteria and assigned weights. MCDM methods were used to select photodetectors used in PET and SPECT systems. One can incorporate as many alternatives and criteria as needed and assign the weights accordingly.

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Stoilova, Svetla Dimitrova. "An Integrated Approach for Selection of Intercity Transport Schemes on Railway Networks." PROMET - Traffic&Transportation 30, no. 4 (2018): 367–77. http://dx.doi.org/10.7307/ptt.v30i4.2673.

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A major problem connected with planning the organization of trains on a railway network is the optimization of the scheme of movement, which determines the routing and the number of trains. In this paper, an integrated approach of fuzzy linear programming method and multi-criteria analysis including three steps is proposed. In the first step, we defined the schemes of transportation of intercity trains and optimized each scheme in terms of direct operating costs by taking into account the uncertainty of passenger flows and utilization of train capacity using the fuzzy linear programming method. In the second step we determined the additional technological criteria to assess the variant schemes. The Fuzzy AHP method was applied to determine the weights of criteria. Using the results obtained from Fuzzy AHP, we prioritized the variant schemes of transportation by applying the PROMETHEE method. The third step presents the optimal choice of transportation of trains on a railway network based on minimum ratio of normalized costs and normalized PROMETHEE net outranking flow. In this step, the model uses the results obtained in the first and second steps. The practicability of the integrated approach is demonstratedthrough the case study of Bulgaria’s railway network, and nine schemes were investigated. The model results and the real situation were compared. It was found out that the optimal scheme of intercity train transportation improves the service and reduces direct operating costs.

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Mahmoudi, Amin. "An Extended Fuzzy PROMETHEE based on Fuzzy Rule based System for Supplier Selection Problem." Indian Journal of Science and Technology 8, no. 1 (2015): 1–11. http://dx.doi.org/10.17485/ijst/2015/v8i31/84225.

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Gul, Muhammet, Erkan Celik, Alev Taskin Gumus, and Ali Fuat Guneri. "A fuzzy logic based PROMETHEE method for material selection problems." Beni-Suef University Journal of Basic and Applied Sciences 7, no. 1 (2018): 68–79. http://dx.doi.org/10.1016/j.bjbas.2017.07.002.

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Peng, Yi, Gang Kou, and Jun Li. "A Fuzzy PROMETHEE Approach for Mining Customer Reviews in Chinese." Arabian Journal for Science and Engineering 39, no. 6 (2014): 5245–52. http://dx.doi.org/10.1007/s13369-014-1033-7.

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El Beggar, Omar. "Multicriteria decision aid for agile methods evaluation using fuzzy PROMETHEE." Journal of Software: Evolution and Process 30, no. 12 (2018): e2108. http://dx.doi.org/10.1002/smr.2108.

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Tian, Xiaojuan, Xiaodong Liu, and Lidong Wang. "An improved PROMETHEE II method based on Axiomatic Fuzzy Sets." Neural Computing and Applications 25, no. 7-8 (2014): 1675–83. http://dx.doi.org/10.1007/s00521-014-1651-8.

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