OWA aggregation with dual preferences for basic uncertain information

2021 ◽  
pp. 1-10
Author(s):  
LeSheng Jin ◽  
Ronald R. Yager ◽  
Jana Špirková ◽  
Radko Mesiar ◽  
Daniel Paternain ◽  
...  
Keyword(s):  
Decision Makers ◽  
Input Vector ◽  
Weighted Averaging ◽  
Preference Aggregation ◽  
Uncertain Information ◽  
Interval Vector ◽  
Owa Operators ◽  
Ordered Weighted Averaging ◽  
Wide Range ◽  
Original Information

Basic Uncertain Information (BUI) as a newly introduced concept generalized a wide range of uncertain information. The well-known Ordered Weighted Averaging (OWA) operators can flexibly and effectively model bipolar preferences of decision makers over given real valued input vector. However, there are no extant methods for OWA operators to be carried out over given BUI vectors. Against this background, this study firstly discusses the interval transformation for BUI and elaborately explains the reasonability within it. Then, we propose the corresponding preference aggregations for BUI in two different decisional scenarios, the aggregation for BUI vector without original information influencing and the aggregation for BUI vector with original information influencing after interval transformation. For each decisional scenario, we also discuss two different orderings of preference aggregation, namely, interval-vector and vector-interval orderings, respectively. Hence, we will propose four different aggregation procedures of preference aggregation for BUI vector. Some illustrative examples are provided immediately after the corresponding aggregation procedures.

GENERALIZED MOVING AVERAGES, DISTANCE MEASURES AND OWA OPERATORS

2013 ◽  
Vol 21 (04) ◽  
pp. 533-559 ◽  
Author(s):  
JOSÉ M. MERIGÓ ◽  
RONALD R. YAGER
Keyword(s):  
Moving Average ◽  
Aggregation Operators ◽  
Distance Measures ◽  
Weighted Averaging ◽  
Owa Operators ◽  
Ordered Weighted Averaging ◽  
Wide Range ◽  
Moving Averaging ◽  
Generalized Distance ◽  
Weighted Moving Average

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 further extend this approach by using distance measures suggesting the concept of distance moving average and generalized distance moving average. We also consider the case with the OWA and the IOWA operator, obtaining the generalized ordered weighted moving averaging distance (GOWMAD) and the induced GOWMAD (IGOWMAD) operator. The paper ends with an application in multi-period decision making.

scholarly journals A Study of OWA Operators Learned in Convolutional Neural Networks

2021 ◽  
Vol 11 (16) ◽  
pp. 7195
Author(s):  
Iris Dominguez-Catena ◽  
Daniel Paternain ◽  
Mikel Galar
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Practical Method ◽  
Local Information ◽  
Weighted Averaging ◽  
Global Information ◽  
Owa Operator ◽  
Owa Operators ◽  
Ordered Weighted Averaging

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 for the OWA operators inside the OWA layer, characterizing them through their basic properties of orness and dispersion. We also compare them to some families of OWA operators, namely the Binomial OWA operator, the Stancu OWA operator and the exponential RIM OWA operator, finding examples that are currently impossible to generalize through these parameterizations.

scholarly journals A method for decision making with the OWA operator

2012 ◽  
Vol 9 (1) ◽  
pp. 357-380 ◽  
Author(s):  
José Merigó ◽  
Anna Gil-Lafuente
Keyword(s):  
Decision Making ◽  
Distance Measures ◽  
Weighted Averaging ◽  
Owa Operator ◽  
Minimum Level ◽  
Ordered Weighted Averaging ◽  
Special Cases ◽  
Wide Range ◽  
Decision Making Problem ◽  
Parameterized Family

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 operators between the minimum and the maximum and a wide range of special cases. Then, the decision maker may take decisions according to his degree of optimism and considering ideals in the decision process. A further extension of this approach is presented by using hybrid averages and Choquet integrals. We also develop an application of the new approach in a multi-person decision-making problem regarding the selection of strategies.

Understanding the Climate-Sensitive Decisions and Information Needs of Freshwater Resource Managers in Hawaii

2013 ◽  
Vol 5 (4) ◽  
pp. 293-308 ◽  
Author(s):  
Melissa L. Finucane ◽  
Rachel Miller ◽  
L. Kati Corlew ◽  
Victoria W. Keener ◽  
Maxine Burkett ◽  
...  
Keyword(s):  
Climate Change ◽  
Information Needs ◽  
Decision Makers ◽  
Uncertain Information ◽  
Climate Information ◽  
Freshwater Resources ◽  
Freshwater Resource ◽  
Wide Range ◽  
Climate Literacy

Abstract Understanding how climate science can be useful in decisions about the management of freshwater resources requires knowledge of decision makers, their climate-sensitive decisions, and the context in which the decisions are being made. A mixed-methods study found that people managing freshwater resources in Hawaii are highly educated and experienced in diverse professions, they perceive climate change as posing a worrisome risk, and they would like to be better informed about how to adapt to climate change. Decision makers with higher climate literacy seem to be more comfortable dealing with uncertain information. Those with lower climate literacy seem to be more trusting of climate information from familiar sources. Freshwater managers in Hawaii make a wide range of climate-sensitive decisions. These decisions can be characterized on several key dimensions including purpose (optimization and evaluation), time horizon (short term and long term), level of information uncertainty (known, uncertain, deeply uncertain, and completely unknown), and information type (quantitative and qualitative). The climate information most relevant to decision makers includes vulnerability assessments incorporating long-term projections about temperature, rainfall distribution, storms, sea level rise, and streamflow changes at an island or statewide scale. The main barriers to using available climate information include insufficient staff time to locate the information and the lack of a clear legal mandate to use the information. Overall, the results suggest that an integrated and systematic approach is needed to determine where and when uncertain climate information is useful and how a larger set of organizational and individual variables affect decision making.

A Study on the Location Analysis Using Spatial Analysis and Ordered Weighted Averaging Operator Weighting Functions

2008 ◽  
Vol 12 (6) ◽  
pp. 529-536 ◽  
Author(s):  
Se-Woong Oh ◽  
◽  
Gyei-Kark Park ◽  
Jong-Min Park ◽  
Sang-Hyun Suh ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Spatial Data ◽  
Fuzzy Ahp ◽  
Selection Method ◽  
Total Order ◽  
Weighted Averaging ◽  
Decision Strategy ◽  
Owa Operators ◽  
Ordered Weighted Averaging ◽  
Definition Of

In this thesis, we proposed the method combining spatial analysis, selection method of weighting values, aggregating decision strategy. To select a sites proposed for ship anchorage, we analyzed spatial data. Fuzzy AHP was used as selection method of weighting values to incorporate the fuzzy set theory and the basic nature of subjectivity due to ambiguity to achieve a flexible decision approach suitable for uncertain and fuzzy environments. To obtain the score that corresponds to the best alternative or the ranking of the alternatives, we need to use a total order for the fuzzy numbers involved in the problem. In this paper, we consider a definition of such a total order: the degree of Orness (1, 3/4, 2/3, 1/2, 1/3, 1/4, 0) reflected with the ordered weighted averaging (OWA) operators. A numerical example was given to illustrate the approach.

scholarly journals INTUITIONISTIC FUZZY GENERALIZED PROBABILISTIC ORDERED WEIGHTED AVERAGING OPERATOR AND ITS APPLICATION TO GROUP DECISION MAKING

2015 ◽  
Vol 22 (2) ◽  
pp. 177-193 ◽  
Author(s):  
Shouzhen ZENG ◽  
Weihua SU ◽  
Chonghui ZHANG
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Averaging ◽  
Uncertain Environments ◽  
Intuitionistic Fuzzy Numbers ◽  
Ordered Weighted Averaging ◽  
Intuitionistic Fuzzy ◽  
Wide Range ◽  
Ordered Weighted Averaging Operator

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 providing a very general formulation that includes a wide range of situations. We study some of its main properties and particular cases such as the generalized intuitionistic fuzzy ordered weighted averaging (GIFOWA) operator and intuitionistic fuzzy probabilistic ordered weighted averaging (IFPOWA) operator. We end the paper by applying the new operator to a group decision making problem concerning the selection of investments.

scholarly journals Three Ways of Defining Owa Operator on the Set of All Normal Convex Fuzzy Sets

2017 ◽  
Vol 69 (1) ◽  
pp. 101-118
Author(s):  
Zdenko Takáč
Keyword(s):  
Fuzzy Sets ◽  
Linear Order ◽  
Recent Literature ◽  
Weighted Averaging ◽  
Owa Operator ◽  
Main Obstacle ◽  
Owa Operators ◽  
Ordered Weighted Averaging ◽  
Algebraic Properties

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 them are also linear.

scholarly journals Applications of ordered weighted averaging (OWA) operators in environmental problems

2017 ◽  
Vol 4 (1) ◽  
pp. 52 ◽  
Author(s):  
Carlos Llopis-Albert ◽  
Daniel Palacios-Marques
Keyword(s):  
Policy Maker ◽  
Aggregation Operator ◽  
Weighted Averaging ◽  
Owa Operators ◽  
Ordered Weighted Averaging ◽  
Degree Of Acceptance ◽  
Environmental Measures ◽  
Water Resources Projects ◽  
Priority Policy ◽  
Different Levels

<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 on the satisfaction of the higher priority policy maker. The methodology establishes a prioritization relationship upon the stakeholders, which preferences are aggregated by means of weights depending on the satisfaction of the higher priority policy maker. The methodology has been successfully applied to a Public Participation Project (PPP) in watershed management, thus obtaining efficient environmental measures in conflict resolution problems under actors’ preference uncertainties.</p>

scholarly journals BiOWA for Preference Aggregation with Bipolar Scales: Application to Fair Optimization in Combinatorial Domains

2019 ◽  
Author(s):  
Hugo Martin ◽  
Patrice Perny
Keyword(s):  
Rating Scales ◽  
Optimization Problems ◽  
Multicriteria Decision Making ◽  
Weighted Averaging ◽  
Preference Aggregation ◽  
Ranking Algorithm ◽  
Pareto Optimal Solutions ◽  
Ordered Weighted Averaging ◽  
Numerical Tests ◽  
Gains And Losses

We study the biOWA model for preference aggregation and multicriteria decision making from bipolar rating scales. A biOWA is an ordered doubly weighted averaging extending standard ordered weighted averaging (OWA) and allowing a finer control of the importance attached to positive and negative evaluations in the aggregation. After establishing some useful properties of biOWA to generate balanced Pareto-optimal solutions, we address fair biOWA-optimization problems in combinatorial domains. We first consider the use of biOWA in multi-winner elections for aggregating graded approval and disapproval judgements. Then we consider the use of biOWA for solving robust path problems with costs expressing gains and losses. A linearization of biOWA is proposed, allowing both problems to be solved by MIP. A path-ranking algorithm for biOWA optimization is also proposed. Numerical tests are provided to show the practical efficiency of our models.

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