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Journal articles on the topic 'Ordered Weighted Averaging (OWA)'

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Published: 2 June 2025

Last updated: 31 July 2025

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1

CHENG, CHING-HSUE, and JING-RONG CHANG. "MCDM AGGREGATION MODEL USING SITUATIONAL ME-OWA AND ME-OWGA OPERATORS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 14, no. 04 (2006): 421–43. http://dx.doi.org/10.1142/s0218488506004102.

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OWA (Ordered Weighted Averaging) aggregation operators have been extensively adopted to handle MCDM (multiple criteria decision making) problems. However, additive or multiplicative preferences should be aggregated with feasible operators. To resolve this problem, this study proposes a new MCDM aggregation model, capable of handling situational group MCDM problems based on the ME-OWA (maximal entropy ordered weighted averaging) and ME-OWGA (maximal entropy ordered weighted geometric averaging) operators. The proposed model is also applied not only to evaluate the service quality of airlines bu

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Figuerola-Wischke, Anton, José M. Merigó, Anna M. Gil-Lafuente, and Josefa Boria-Reverter. "A Bibliometric Review of the Ordered Weighted Averaging Operator." Mathematics 12, no. 7 (2024): 1053. http://dx.doi.org/10.3390/math12071053.

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The ordered weighted averaging (OWA) operator was proposed by Yager back in 1988 and constitutes a parameterized family of aggregation functions between the minimum and the maximum. The purpose of this paper is to perform a bibliometric review of this aggregation operator during the last 35 years through the Web of Science (WoS) Core Collection database and the Visualization of Similarities (VOS) viewer software. The results show that the OWA operator is an increasingly popular aggregation operator, especially in Computer Science. The results also allow the assertion that Yager, as expected, i

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Emrouznejad, Ali. "SAS/OWA: ordered weighted averaging in SAS optimization." Soft Computing 14, no. 4 (2009): 379–86. http://dx.doi.org/10.1007/s00500-009-0411-7.

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Aragón, Roberto G., Jesús Medina, Samuel Molina-Ruiz, and Ronald R. Yager. "On the Complete Lattice Structure of Ordered Functional Weighted Averaging Operators." Mathematics 13, no. 5 (2025): 795. https://doi.org/10.3390/math13050795.

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Ordered functional weighted averaging (OFWA) operators are a generalization of the well-known ordered weighted averaging (OWA) operators in which functions, instead of single values, are considered as weights. This fact offers an extra level of flexibility; for example, in multi-criteria decision-making, it can be used to aggregate available information and provide recommendations. This paper furthers the analysis of these general operators, studying how they can be combined to obtain conservative and aggressive perspectives from experts and studying the algebraic structure of the whole set of

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Merigo, José M., Kurt J. Engemann, and Daniel Palacios-Marques. "DECISION MAKING WITH DEMPSTER-SHAFER BELIEF STRUCTURE AND THE OWAWA OPERATOR." Technological and Economic Development of Economy 19, Supplement_1 (2014): S100—S118. http://dx.doi.org/10.3846/20294913.2013.869517.

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A new decision making model that uses the weighted average and the ordered weighted averaging (OWA) operator in the Dempster-Shafer belief structure is presented. Thus, we are able to represent the decision making problem considering objective and subjective information and the attitudinal character of the decision maker. For doing so, we use the ordered weighted averaging – weighted average (OWAWA) operator. It is an aggregation operator that unifies the weighted average and the OWA in the same formulation. This approach is generalized by using quasi-arithmetic means and group decision making

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MERIGÓ, JOSÉ M., and RONALD R. YAGER. "GENERALIZED MOVING AVERAGES, DISTANCE MEASURES AND OWA OPERATORS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 21, no. 04 (2013): 533–59. http://dx.doi.org/10.1142/s0218488513500268.

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The concept of moving average is studied. We analyze several extensions by using generalized aggregation operators, obtaining the generalized moving average. The main advantage is that it provides a general framework that includes a wide range of specific cases including the geometric and the quadratic moving average. This analysis is extended by using the generalized ordered weighted averaging (GOWA) and the induced GOWA (IGOWA) operator. Thus, we get the generalized ordered weighted moving average (GOWMA) and the induced GOWMA (IGOWMA) operator. Some of their main properties are studied. We

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Tesfamariam, Solomon, and Rehan Sadiq. "Probabilistic risk analysis using ordered weighted averaging (OWA) operators." Stochastic Environmental Research and Risk Assessment 22, no. 1 (2006): 1–15. http://dx.doi.org/10.1007/s00477-006-0090-1.

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Alfaro-García, Víctor G., Fabio Blanco-Mesa, Ernesto León-Castro, and Jose M. Merigo. "Bonferroni Weighted Logarithmic Averaging Distance Operator Applied to Investment Selection Decision Making." Mathematics 10, no. 12 (2022): 2100. http://dx.doi.org/10.3390/math10122100.

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Distance measures in ordered weighted averaging (OWA) operators allow the modelling of complex decision making problems where a set of ideal values or characteristics are required to be met. The objective of this paper is to introduce extended distance measures and logarithmic OWA-based decision making operators especially designed for the analysis of financial investment options. Based on the immediate weights, Bonferroni means and logarithmic averaging operators, in this paper we introduce the immediate weights logarithmic distance (IWLD), the immediate weights ordered weighted logarithmic a

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Faramarzi, Hassan, Seyed Mohsen Hosseini, Hamid Reza Pourghasemi, and Mahdi Farnaghi. "Forest fire spatial modelling using ordered weighted averaging multi-criteria evaluation." Journal of Forest Science 67, No. 2 (2021): 87–100. http://dx.doi.org/10.17221/50/2020-jfs.

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Forest fires are a major environmental issue because they are increasing as a consequence of climate change and global warming. The present study was aimed to model forest fire hazard using the ordered weighted averaging (OWA) multi-criteria evaluation algorithm and to determine the role of human, climatic, and environmental factors in forest fire occurrence within the Golestan National Park (GNP), Iran. The database used for the present study was created according to daily classification of climate changes, environmental basic maps, and human-made influential forest fire factors. In the study

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De Miguel, Laura, Daniel Paternain, Inmaculada Lizasoain, Gustavo Ochoa, and Humberto Bustince. "Some Characterizations of Lattice OWA Operators." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 25, Suppl. 1 (2017): 5–17. http://dx.doi.org/10.1142/s0218488517400013.

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Ordered Weighted Averaging (OWA) operators are a family of aggregation functions for data fusion. If the data are real numbers, then OWA operators can be characterized either as a special kind of discrete Choquet integral or simply as an arithmetic mean of the given values previously ordered. This paper analyzes the possible generalizations of these characterizations when OWA operators are defined on a complete lattice. In addition, the set of all n-ary OWA operators is studied as a sublattice of the lattice of all the n-ary aggregation functions defined on a distributive lattice.

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MERIGÓ, JOSÉ M., and MONTSERRAT CASANOVAS. "THE UNCERTAIN GENERALIZED OWA OPERATOR AND ITS APPLICATION TO FINANCIAL DECISION MAKING." International Journal of Information Technology & Decision Making 10, no. 02 (2011): 211–30. http://dx.doi.org/10.1142/s0219622011004300.

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We introduce the uncertain generalized OWA (UGOWA) operator. This operator is an extension of the OWA operator that uses generalized means and uncertain information represented as interval numbers. By using UGOWA, it is possible to obtain a wide range of uncertain aggregation operators such as the uncertain average (UA), the uncertain weighted average (UWA), the uncertain OWA (UOWA) operator, the uncertain ordered weighted geometric (UOWG) operator, the uncertain ordered weighted quadratic averaging (UOWQA) operator, the uncertain generalized mean (UGM), and many specialized operators. We stud

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Chen, Yi-Fang, and Hui-Chin Tang. "A Three-Dimensional Constrained Ordered Weighted Averaging Aggregation Problem with Lower Bounded Variables." Symmetry 10, no. 8 (2018): 339. http://dx.doi.org/10.3390/sym10080339.

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We consider the constrained ordered weighted averaging (OWA) aggregation problem with a single constraint and lower bounded variables. For the three-dimensional constrained OWA aggregation problem with lower bounded variables, we present four types of solution(x1',x2',x3') depending on the number of zero elements. According to the computerized experiment we perform, the lower bounds can affect the solution(x1',x2',x3') types, thereby affecting the optimal solution of the three-dimensional constrained OWA aggregation problem with lower bounded variables.

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Rigopoulos, Georgios. "Weighted OWA (Ordered Weighted Averaging Operator) Preference Aggregation for Group Multicriteria Decisions." International Journal of Computational and Applied Mathematics & Computer Science 3 (May 8, 2023): 10–17. http://dx.doi.org/10.37394/232028.2023.3.2.

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Group decision making is an integral part of operations and management functions in almost every business domain with substantial applications in finance and economics. In parallel to human decision makers, software agents operate in business systems and environments, collaborate, compete and perform algorithmic decision-making tasks as well. In both settings, information aggregation of decision problem parameters and agent preferences is a necessary step to generate group decision outcome. Although plenty aggregation information approaches exist, overcomplexity of the underlying aggregating o

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ZENG, Shouzhen, Weihua SU, and Chonghui ZHANG. "INTUITIONISTIC FUZZY GENERALIZED PROBABILISTIC ORDERED WEIGHTED AVERAGING OPERATOR AND ITS APPLICATION TO GROUP DECISION MAKING." Technological and Economic Development of Economy 22, no. 2 (2015): 177–93. http://dx.doi.org/10.3846/20294913.2014.984253.

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In this paper, we present the intuitionistic fuzzy generalized probabilistic ordered weighted averaging (IFGPOWA) operator. It is a new aggregation operator that uses generalized means in a unified model between the probability and the OWA operator. The main advantage of this new operator is that it is able to deal with probabilities (objective information) and ordered weighted averages (subjective information) in the same formulation. Moreover, it is also able to deal with uncertain environments that can be assessed with intuitionistic fuzzy numbers. Furthermore, it uses generalized means pro

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Rinner, Claus, and Jacek Malczewski. "Web-enabled spatial decision analysis using Ordered Weighted Averaging (OWA)." Journal of Geographical Systems 4, no. 4 (2002): 385–403. http://dx.doi.org/10.1007/s101090300095.

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Llopis-Albert, Carlos, and Daniel Palacios-Marques. "Applications of ordered weighted averaging (OWA) operators in environmental problems." Multidisciplinary Journal for Education, Social and Technological Sciences 4, no. 1 (2017): 52. http://dx.doi.org/10.4995/muse.2017.7001.

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<p>This paper presents an application of a prioritized weighted aggregation operator based on ordered weighted averaging (OWA) to deal with stakeholders' constructive participation in water resources projects. They have different degree of acceptance or preference regarding the measures and policies to be carried out, which lead to different environmental and socio-economic outcomes, and hence, to different levels of stakeholders’ satisfaction. The methodology establishes a prioritization relationship upon the stakeholders, which preferences are aggregated by means of weights depending o

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Pons-Vives, Pere Josep, Mateu Morro-Ribot, Carles Mulet-Forteza, and Oscar Valero. "An Application of Ordered Weighted Averaging Operators to Customer Classification in Hotels." Mathematics 10, no. 12 (2022): 1987. http://dx.doi.org/10.3390/math10121987.

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An algorithm widely used in hotel companies for demand analysis is the so-called K-means. The aforementioned algorithm is based on the use of the Euclidean distance as a dissimilarity measure and this fact can cause a main handicap. Concretely, the Euclidean distance provides a global difference measure between the values of the descriptive variables that can blur the relative differences in each component separately and, hence, the cluster algorithm can assign a custom to an incorrect cluster. In order to avoid this drawback, this paper proposes an application of the use of Ordered Weighted A

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Robinson, John, and Henry Amirtharaj. "Efficient Multiple Attribute Group Decision Making Models with Correlation Coefficient of Vague Sets." International Journal of Operations Research and Information Systems 5, no. 3 (2014): 27–49. http://dx.doi.org/10.4018/ijoris.2014070102.

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A new approach for multiple attribute group decision making (MAGDM) problems where the attribute weights and the expert weights are real numbers and the attribute values take the form of vague values, is presented in this paper. Since families of ordered weighted averaging (OWA) operators are available in the literature, and only a few available for vague sets, the vague ordered weighted averaging (VOWA) operator and the induced vague ordered weighted averaging (IVOWA) operator are introduced in this paper and utilized for aggregating the vague information. The correlation coefficient for vagu

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Su, Weihua, Shouzhen Zeng, and Xiaojia Ye. "UNCERTAIN GROUP DECISION-MAKING WITH INDUCED AGGREGATION OPERATORS AND EUCLIDEAN DISTANCE." Technological and Economic Development of Economy 19, no. 3 (2013): 431–47. http://dx.doi.org/10.3846/20294913.2013.821686.

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In this paper, we present the induced uncertain Euclidean ordered weighted averaging distance (IUEOWAD) operator. It is an extension of the OWA operator that uses the main characteristics of the induced OWA (IOWA), the Euclidean distance and uncertain information represented by interval numbers. The main advantage of this operator is that it is able to consider complex attitudinal characters of the decision-maker by using order-inducing variables in the aggregation of the Euclidean distance. Moreover, it is able to deal with uncertain environments where the information is very imprecise and ca

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Malczewski, Jacek, Terry Chapman, Cindy Flegel, Dan Walters, Dan Shrubsole, and Martin A. Healy. "GIS–Multicriteria Evaluation with Ordered Weighted Averaging (OWA): Case Study of Developing Watershed Management Strategies." Environment and Planning A: Economy and Space 35, no. 10 (2003): 1769–84. http://dx.doi.org/10.1068/a35156.

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This paper focuses on the parameterized-ordered weighted averaging (OWA) method. OWA is a family of multicriteria evaluation (or combination) rules. The proposed approach uses a parameter that serves as a mechanism for guiding multicriteria evaluation procedures. The parameter is incorporated into a method for obtaining the optimal order weights and for developing a transformation function. The function provides us with a consistent way of modifying the criterion values so that the multicriteria combination procedures can be guided by specifying a single parameter. The parameterized-OWA method

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Harmati, István Á., Norbert Kovács, Dávid Fülep, and Krisztián Koppány. "OWA operators in the insurance industry." Journal of Infrastructure, Policy and Development 8, no. 13 (2024): 8015. http://dx.doi.org/10.24294/jipd8015.

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In this paper, we examine a possible application of ordered weighted average (OWA for short) aggregation operators in the insurance industry. Aggregation operators are essential tools in decision-making when a single value is needed instead of a couple of features. Information aggregation necessarily leads to information loss, at least to a specific extent. Whether we concentrate on extreme values or middle terms, there can be cases when the most important piece of the puzzle is missing. Although the simple or weighted mean considers all the values there is a drawback: the values get the same

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Ruan, Chuanyang, Xiangjing Chen, and Lin Yan. "Fermatean Hesitant Fuzzy Multi-Attribute Decision-Making Method with Probabilistic Information and Its Application." Axioms 13, no. 7 (2024): 456. http://dx.doi.org/10.3390/axioms13070456.

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When information is incomplete or uncertain, Fermatean hesitant fuzzy sets (FHFSs) can provide more information to help decision-makers deal with more complex problems. Typically, determining attribute weights assumes that each attribute has a fixed influence. Introducing probability information can enable one to consider the stochastic nature of evaluation data and better quantify the importance of the attributes. To aggregate data by considering the location and importance degrees of each attribute, this paper develops a Fermatean hesitant fuzzy multi-attribute decision-making (MADM) method

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Kreinovich, Vladik. "Ordered Weighted Averaging (OWA), Decision Making under Uncertainty, and Deep Learning: How Is This All Related?" Information 13, no. 2 (2022): 82. http://dx.doi.org/10.3390/info13020082.

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Among many research areas to which Ron Yager contributed are decision making under uncertainty (in particular, under interval and fuzzy uncertainty) and aggregation—where he proposed, analyzed, and utilized ordered weighted averaging (OWA). The OWA algorithm itself provides only a specific type of data aggregation. However, it turns out that if we allow several OWA stages, one after another, we obtain a scheme with a universal approximation property—moreover, a scheme which is perfectly equivalent to modern ReLU-based deep neural networks. In this sense, Ron Yager can be viewed as a (grand)fat

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Ghasemkhani, Neda, Saeideh Sahebi Vayghan, Abolfazl Abdollahi, Biswajeet Pradhan, and Abdullah Alamri. "Urban Development Modeling Using Integrated Fuzzy Systems, Ordered Weighted Averaging (OWA), and Geospatial Techniques." Sustainability 12, no. 3 (2020): 809. http://dx.doi.org/10.3390/su12030809.

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This paper proposes a model to identify the changing of bare grounds into built-up or developed areas. The model is based on the fuzzy system and the Ordered Weighted Averaging (OWA) methods. The proposed model consists of four main sections, which include physical suitability, accessibility, the neighborhood effect, and a calculation of the overall suitability. In the first two parts, physical suitability and accessibility were obtained by defining fuzzy inference systems and applying the required map data associated with each section. However, in order to calculate the neighborhood effect, w

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Merigó, José, and Anna Gil-Lafuente. "A method for decision making with the OWA operator." Computer Science and Information Systems 9, no. 1 (2012): 357–80. http://dx.doi.org/10.2298/csis110206044m.

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A new method for decision making that uses the ordered weighted averaging (OWA) operator in the aggregation of the information is presented. It is used a concept that it is known in the literature as the index of maximum and minimum level (IMAM). This index is based on distance measures and other techniques that are useful for decision making. By using the OWA operator in the IMAM, we form a new aggregation operator that we call the ordered weighted averaging index of maximum and minimum level (OWAIMAM) operator. The main advantage is that it provides a parameterized family of aggregation oper

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Xian, Sidong. "Fuzzy Linguistic Induced Ordered Weighted Averaging Operator and Its Application." Journal of Applied Mathematics 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/210392.

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With respect to multiple attribute group decision making (MAGDM) problems, in which the attribute weights take the form of real numbers, and the attribute values take the form of fuzzy linguistic scale variables, a decision analysis approach is proposed. In this paper, we develop a new fuzzy linguistic induce OWA (FLIOWA) operator and analyze the properties of it by utilizing some operational laws of fuzzy linguistic scale variables. A method based on the FLIOWA operators for multiple attribute group decision making is presented. Finally, a numerical example is used to illustrate the applicabi

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Mitchell, H. B., and D. D. Estrakh. "A Modified OWA Operator and its Use in Lossless DPCM Image Compression." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 05, no. 04 (1997): 429–36. http://dx.doi.org/10.1142/s0218488597000324.

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The ordered weighted averaging (OWA) operator of Yager was introduced to provide a method for aggregating several inputs which lies between the Max and Min operators. The fundamental aspect of the OWA operator is a reordering step in which the input arguments are re-arranged according to their actual relative value. In this paper we describe a modified OWA operator in which the input arguments are not re-arranged according to their actual relative values but rather according to their estimated relative values. We describe an unusual application of this operator to lossless image compression.

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HONG, DUG HUN. "A NOTE ON THE MINIMAL VARIABILITY OWA OPERATOR WEIGHTS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 14, no. 06 (2006): 747–52. http://dx.doi.org/10.1142/s0218488506004308.

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One important issue in the theory of ordered weighted averaging (OWA) operators is the determination of the associated weighting vector. Recently, Fullér and Majlender2 derived the minimal variability weighting vector for any level of orness using the Kuhn-Tucker second-order sufficiency conditions for optimality. In this note, we give a new proof of the problem.

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LI, DENG-FENG, LI-LING WANG, and GUO-HONG CHEN. "GROUP DECISION MAKING METHODOLOGY BASED ON THE ATANASSOV'S INTUITIONISTIC FUZZY SET GENERALIZED OWA OPERATOR." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 18, no. 06 (2010): 801–17. http://dx.doi.org/10.1142/s0218488510006805.

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The aim of this paper is to develop a new methodology for solving group decision making problems in which preference comparisons between alternatives are expressed with Atanassov's intuitionistic fuzzy (IF) preference relations. In this methodology, the generalized ordered weighted averaging (GOWA) operator is extended to develop the Atanassov's IF set (IFS) generalized ordered weighted averaging (IFSGOWA) operator, which can aggregate vague or imprecise information expressed with the Atanassov's IFSs. The Atanassov's IFSGOWA operator based methodology is further developed to solve group decis

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Zabihi, Hasan, Mohsen Alizadeh, Philip Kibet Langat, et al. "GIS Multi-Criteria Analysis by Ordered Weighted Averaging (OWA): Toward an Integrated Citrus Management Strategy." Sustainability 11, no. 4 (2019): 1009. http://dx.doi.org/10.3390/su11041009.

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This study proposes a site location assessment model for citrus cropland using multi-criteria evaluation (MCE) and the combination of a set of factors for suitability mapping and delineating the suitable areas for citrus production in Ramsar, Iran. It defines an incorporated method for the suitability mapping of the most appropriate sites for citrus cultivars with an emphasis on the multi-criteria decision analysis (MCDA) process. The combination of geographic information system (GIS) and a modified version of the analytic hierarchy process (AHP) based on the ordered weighted averaging (OWA) t

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Prasetyo, Aries Alfian, Suprapedi Suprapedi, Siska Narulita, and Bayu Praharsena. "Metode K-Means Berbasis Ordered Weighted Averaging (OWA) pada Data Potensi Desa untuk Penentuan Status Desa." JBE (Jurnal Bingkai Ekonomi) 7, no. 2 (2022): 76–91. http://dx.doi.org/10.54066/jbe.v7i2.224.

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Indeks Pembangunan Desa yang dibangun dari Pendataan Potensi Desa (Podes) tahun 2014. untuk menilai tingkat perkembangan desa, dibagi menjadi 3 klasifikasi yaitu Desa Mandiri, Berkembang, dan Tertinggal, memiliki 5 dimensi. Penulis bertujuan untuk menilai tingkat perkembangan desa melalui status desa berdasar data IPD, penentuan status desa menggunakan teknik clustering dengan metode K-Means berbasis Ordered Weighted Averaging (OWA), OWA dapat mengurangi kompleksitas data dengan memadukan nilai multi attribut ke nilai agregat berupa nilai tunggal dengan menggunakan expert judgement untuk menen

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Yin, Die, Taifu Li, and Zhiqiang Liao. "Research on the Evaluation Modeling Method of User Experience Quality under Uncertain Noise Environment." Mathematical Problems in Engineering 2020 (December 7, 2020): 1–13. http://dx.doi.org/10.1155/2020/7940645.

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Experience economy is a trend of future economic development. Enterprises can only occupy the market more successfully by enhancing the user experience in product design. The user’s product experience is affected by uncertainty noises (such as the user’s environment and different users), rendering the user experience quality evaluation results highly variable. The purpose of this paper is to study the modeling method of user experience quality evaluations under uncertain environmental noises; inspired by normal ordered weighted averaging (OWA) operators, the normal distribution probability den

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Ogryczak, Włodzimierz, and Paweł Olender. "On MILP Models for the OWA Optimization." Journal of Telecommunications and Information Technology, no. 2 (June 30, 2012): 5–12. http://dx.doi.org/10.26636/jtit.2012.2.1259.

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The problem of aggregating multiple outcomes to form overall objective functions is of considerable importance in many applications. The ordered weighted averaging (OWA) aggregation uses the weights assigned to the ordered values (i.e., to the largest value, the second largest and so on) rather than to the specific coordinates. It allows to evaluate solutions impartially, when distribution of outcomes is more important than assignments these outcomes to the specific criteria. This applies to systems with multiple independent users or agents, whose objectives correspond to the criteria. The ord

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Sadiq, Rehan, and Solomon Tesfamariam. "Developing environmental indices using fuzzy numbers ordered weighted averaging (FN-OWA) operators." Stochastic Environmental Research and Risk Assessment 22, no. 4 (2007): 495–505. http://dx.doi.org/10.1007/s00477-007-0151-0.

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Zeng, Shouzhen, Jianping Chen, and Xingsen Li. "A Hybrid Method for Pythagorean Fuzzy Multiple-Criteria Decision Making." International Journal of Information Technology & Decision Making 15, no. 02 (2016): 403–22. http://dx.doi.org/10.1142/s0219622016500012.

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As a generalization of intuitionistic fuzzy set, the Pythagorean fuzzy set is interesting and very useful in modeling uncertain information in real-world decision-making problems. In this paper, we develop a new method for Pythagorean fuzzy multiple-criteria decision-making (MCDM) problems with aggregation operators and distance measures. First, we present the Pythagorean fuzzy ordered weighted averaging weighted average distance (PFOWAWAD) operator. The main advantage of the PFOWAWAD operator is that it uses distance measures in a unified framework between the ordered weighted averaging (OWA)

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Ogryczak, Włodzimierz, and Tomasz Śliwiński. "Decision Support under Risk by Optimization of Scenario Importance Weighted OWA Aggregations." Journal of Telecommunications and Information Technology, no. 3 (June 26, 2023): 5–13. http://dx.doi.org/10.26636/jtit.2009.3.933.

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The problem of evaluation outcomes under several scenarios to form overall objective functions is of considerable importance in decision support under uncertainty. The fuzzy operator defined as the so-called weighted OWA (WOWA) aggregation offers a well-suited approach to this problem. The WOWA aggregation, similar to the classical ordered weighted averaging (OWA), uses the preferential weights assigned to the ordered values (i.e., to the worst value, the second worst and so on) rather than to the specific criteria. This allows one to model various preferences with respect to the risk. Simulta

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Dominguez-Catena, Iris, Daniel Paternain, and Mikel Galar. "A Study of OWA Operators Learned in Convolutional Neural Networks." Applied Sciences 11, no. 16 (2021): 7195. http://dx.doi.org/10.3390/app11167195.

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Ordered Weighted Averaging (OWA) operators have been integrated in Convolutional Neural Networks (CNNs) for image classification through the OWA layer. This layer lets the CNN integrate global information about the image in the early stages, where most CNN architectures only allow for the exploitation of local information. As a side effect of this integration, the OWA layer becomes a practical method for the determination of OWA operator weights, which is usually a difficult task that complicates the integration of these operators in other fields. In this paper, we explore the weights learned

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Noth, Tanner, and Claus Rinner. "Prioritization in wildfire restoration using GIS-based ordered weighted averaging (OWA): A case study in southern California." AIMS Environmental Science 8, no. 5 (2021): 481–97. http://dx.doi.org/10.3934/environsci.2021031.

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<abstract> <p>Wildfires are a prevalent natural disaster that can significantly impact human populations and result in considerable losses. With a changing climate, wildfires in many countries have increased in intensity and frequency, making effective restoration efforts in affected areas crucial. This paper aims to evaluate the efficacy of ordered weighted averaging (OWA), a GIS-based multi-criteria decision analysis technique, in identifying priority areas for wildfire restoration. A case study using the 2009 Station Fire in California is presented, using the restoration criteri

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Coşkun, Efsun, Resmiye Nasiboglu, and Baris Tekin Tezel. "An approach to obtain the generalized mixed linear stress function for known owa weights with artificial bee colony algorithm." Global Journal of Information Technology: Emerging Technologies 6, no. 3 (2017): 150–57. http://dx.doi.org/10.18844/gjit.v6i3.1880.

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Abstract OWA (Ordered Weighted Averaging) is a flexible aggregation operator which is come up with Yager to create a decision function in multi-criteria decision making. It is possible to determine how optimistic or pessimistic the decision maker's opinion with the value obtained from the weights of this operator. The determination of OWA weights cannot provide characterization by itself. If it is desired to aggregate various sized objects in terms of generalization and reusability of OWA weights, a more general form is needed. In this study, we propose the parameterized piecewise linear

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Xian, Sidong, Wenting Xue, Jianfeng Zhang, Yubo Yin, and Qin Xie. "Intuitionistic Fuzzy Linguistic Induced Ordered Weighted Averaging Operator for Group Decision Making." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 23, no. 04 (2015): 627–48. http://dx.doi.org/10.1142/s0218488515500270.

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With respect to multiple attribute group decision making (MAGDM) problems, in which the attribute weights take the form of real numbers, and the attribute values take the form of intuitionistic fuzzy linguistic variables, a decision analysis approach is proposed. In this paper, we develop an intuitionistic fuzzy linguistic induce OWA (IFLIOWA) operator and analyze the properties of it by utilizing some operational laws of intuitionistic fuzzy linguistic variables. A new method based on the IFLIOWA operator for multiple attribute group decision making (MAGDM) is presented. Finally, a numerical

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Malczewski, Jacek. "Integrating multicriteria analysis and geographic information systems: the ordered weighted averaging (OWA) approach." International Journal of Environmental Technology and Management 6, no. 1/2 (2006): 7. http://dx.doi.org/10.1504/ijetm.2006.008251.

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Hong, Dug Hun. "The General Model for Least Convex Disparity RIM Quantifier Problems." Mathematics 7, no. 7 (2019): 576. http://dx.doi.org/10.3390/math7070576.

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Hong (Mathematics 2019, 7, 326) recently introduced the general least squares deviation (LSD) model for ordered weighted averaging (OWA) operator weights. In this paper, we propose the corresponding generalized least square disparity model for regular increasing monotone (RIM) quantifier determination under a given orness level. We prove this problem mathematically. Using this result, we provide the full solution of the least square disparity RIM quantifier model as an illustrative example.

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Scherger, Valeria, Antonio Terceño, and Hernán Vigier. "The OWA distance operator and its application in business failure." Kybernetes 46, no. 1 (2017): 114–30. http://dx.doi.org/10.1108/k-05-2016-0107.

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Purpose The purpose of this paper is to develop a goodness index based on Hamming distance and ordered weighted averaging distance (OWAD), which is useful to make decisions. These alternative measures enrich the results of diagnostic fuzzy models and facilitate the experts’ task in decision-making. An application to a set of firms to verify the results is also presented. Design/methodology/approach The paper follows the basis of OWA operators to design a methodology to reduce the map of causes of business failure into monitoring key areas. Findings The present paper introduces two alternative

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de Jesus, Gildson Queiroz, and Eduardo Silva Palmeira. "Least Squares in a Data Fusion Scenario via Aggregation Operators." Axioms 11, no. 12 (2022): 678. http://dx.doi.org/10.3390/axioms11120678.

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In this paper, appropriate least-squares methods were developed to operate in data fusion scenarios. These methods generate optimal estimates by combining measurements from a finite collection of samples. The aggregation operators of the average type, namely, ordered weighted averaging (OWA), Choquet integral, and mixture operators, were applied to formulate the optimization problem. Numerical examples about fitting curves to a given set of points are provided to show the effectiveness of the proposed algorithms.

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Zhao, Bobo, Tao Tang, and Bin Ning. "Applying Hybrid Decision-Making Method Based on Fuzzy AHP-WOWA Operator for Emergency Alternative Evaluation of Unattended Train Operation Metro System." Mathematical Problems in Engineering 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/4105079.

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Optimal alternative selection to address the emergency situation is critical for dispatcher group in Unattended Train Operation (UTO) to guide emergency process. It is difficult to provide the precise decision value under one criterion and to evaluate the emergency alternatives among multiple dispatchers. This paper presents a hybrid emergency decision-making method integrating fuzzy analytic hierarchy process (FAHP) described by linguistic terms with enhanced weighted ordered weighted averaging (WOWA) operator. The enhanced WOWA operator aggregates the preference matrices of multidispatcher t

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Vizuete-Luciano, Emili, Sefa Boria-Reverter, José M. Merigó-Lindahl, Anna Maria Gil-Lafuente, and Maria Luisa Solé-Moro. "Fuzzy Branch-and-Bound Algorithm with OWA Operators in the Case of Consumer Decision Making." Mathematics 9, no. 23 (2021): 3045. http://dx.doi.org/10.3390/math9233045.

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The ordered weighted averaging (OWA) operator is one of the most used techniques in the operator’s aggregation procedure. This paper proposes a new assignment algorithm by using the OWA operator and different extensions of it in the Branch-and-bound algorithm. The process is based on the use of the ordered weighted average distance operator (OWAD) and the induced OWAD operator (IOWAD). We present it as the Branch-and-bound algorithm with the OWAD operator (BBAOWAD) and the Branch-and-bound algorithm with the IOWAD operator (BBAIOWAD). The main advantage of this approach is that we can obtain m

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Kazemi, Enseih, Danial Sadrian Zadeh, and Behzad Moshiri. "Metal-oxide-semiconductor Sensors Modeling Using Ordered Weighted Averaging (OWA) Operators in Electronic Nose." Measurement 184 (November 2021): 109932. http://dx.doi.org/10.1016/j.measurement.2021.109932.

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Yilmaz, Murat. "The Selection of a Children's Librarian: OWA (Ordered Weighted Averaging) as a New Model." Journal of Library Administration 54, no. 7 (2014): 573–89. http://dx.doi.org/10.1080/01930826.2014.964018.

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Pereira Libório, Matheus, Petr Iakovlevitch Ekel, Sandro Laudares, and Carlos Augusto Paiva da Silva Martins. "A goal-based weighting for composite indicators constructed through Ordered Weighted Averaging (OWA) operator." MethodsX 12 (June 2024): 102575. http://dx.doi.org/10.1016/j.mex.2024.102575.

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Takáč, Zdenko. "Three Ways of Defining Owa Operator on the Set of All Normal Convex Fuzzy Sets." Tatra Mountains Mathematical Publications 69, no. 1 (2017): 101–18. http://dx.doi.org/10.1515/tmmp-2017-0017.

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Abstract We deal with an extension of ordered weighted averaging (OWA, for short) operators to the set of all normal convex fuzzy sets in [0, 1]. The main obstacle to achieve this goal is the non-existence of a linear order for fuzzy sets. Three ways of dealing with the lack of a linear order on some set and defining OWA operators on the set appeared in the recent literature. We adapt the three approaches for the set of all normal convex fuzzy sets in [0, 1] and study their properties. It is shown that each of the three approaches leads to operator with desired algebraic properties, and two of

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