214 research outputs found

    The induced 2-tuple linguistic generalized OWA operator and its application in linguistic decision making

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    We present the induced 2-tuple linguistic generalized ordered weighted averaging (2-TILGOWA) operator. This new aggregation operator extends previous approaches by using generalized means, order-inducing variables in the reordering of the arguments and linguistic information represented with the 2-tuple linguistic approach. Its main advantage is that it includes a wide range of linguistic aggregation operators. Thus, its analyses can be seen from different perspectives and we obtain a much more complete picture of the situation considered and are able to select the alternative that best fits with with our interests or beliefs. We further generalize the operator by using quasi-arithmetic means, and obtain the Quasi-2-TILOWA operator. We conclude this paper by analysing the applicability of this new approach in a decision-making problem concerning product management.linguistic decision making, linguistic generalized mean, 2-tuple linguistic owa operator, 2-tuple linguistic aggregation operator

    Single machine scheduling problems with uncertain parameters and the OWA criterion

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    In this paper a class of single machine scheduling problems is discussed. It is assumed that job parameters, such as processing times, due dates, or weights are uncertain and their values are specified in the form of a discrete scenario set. The Ordered Weighted Averaging (OWA) aggregation operator is used to choose an optimal schedule. The OWA operator generalizes traditional criteria in decision making under uncertainty, such as the maximum, average, median or Hurwicz criterion. It also allows us to extend the robust approach to scheduling by taking into account various attitudes of decision makers towards the risk. In this paper a general framework for solving single machine scheduling problems with the OWA criterion is proposed and some positive and negative computational results for two basic single machine scheduling problems are provided

    "The connection between distortion risk measures and ordered weighted averaging operators"

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    Distortion risk measures summarize the risk of a loss distribution by means of a single value. In fuzzy systems, the Ordered Weighted Averaging (OWA) and Weighted Ordered Weighted Averaging (WOWA) operators are used to aggregate a large number of fuzzy rules into a single value. We show that these concepts can be derived from the Choquet integral, and then the mathematical relationship between distortion risk measures and the OWA and WOWA operators for discrete and nite random variables is presented. This connection oers a new interpretation of distortion risk measures and, in particular, Value-at-Risk and Tail Value-at-Risk can be understood from an aggregation operator perspective. The theoretical results are illustrated in an example and the degree of orness concept is discussed.Fuzzy systems; Degree of orness; Risk quantification; Discrete random variable JEL classification:C02,C60

    Decision making in reinsurance with induced OWA operators and Minkowski distances

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    The decision to choose a reinsurance program has many complexities because it is difficult to simultaneously achieve high levels in different optimal criteria including maximum gain, minimum variance, and probability of ruin. This article suggests a new method by which, through membership functions, we can measure the distance of each alternative to an optimal result and aggregate it by using different types of aggregations. In this article, particular attention is given to the induced Minkowski ordered weighted averaging distance operator and the induced Minkowski probabilistic ordered weighted averaging distance operator. The main advantage of these operators is that they include a wide range of special cases. Thus, they can adapt efficiently to the specific needs of the calculation processes. By doing so, the reinsurance system can make better decisions by using different scenarios in the uncertain environment considered

    The induced generalized OWA operator

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    We present the induced generalized ordered weighted averaging (IGOWA) operator. It is a new aggregation operator that generalizes the OWA operator by using the main characteristics of two well known aggregation operators: the generalized OWA and the induced OWA operator. Then, this operator uses generalized means and order inducing variables in the reordering process. With this formulation, we get a wide range of aggregation operators that include all the particular cases of the IOWA and the GOWA operator, and a lot of other cases such as the induced ordered weighted geometric (IOWG) operator and the induced ordered weighted quadratic averaging (IOWQA) operator. We further generalize the IGOWA operator by using quasi-arithmetic means. The result is the Quasi-IOWA operator. Finally, we also develop a numerical example of the new approach in a financial decision making problem

    On the relationships between some games associated with SUOWA and Semi-SUOWA operators

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    Producción CientíficaThe construction of functions that simultaneously generalize weighted means and OWA operators is an interesting topic that has received special attention in recent years. Due to the properties they satisfy, one of the most interesting generalization are SUOWA operators, which have been widely studied in the literature. In a recent paper, a new generalization has been introduced, the Semi-SUOWA operators, which have a close relationship with SUOWA operators. The main aim of this paper is to analyze the games associated with Semi-SUOWA operators. In this respect, we give conditions under which we can guarantee the monotonicity of these games. Moreover, we establish some relationships between some games associated with SUOWA and Semi-SUOWA operators and show the pointwise convergence of certain games.Este trabajo forma parte del proyecto de investigación: MEC-FEDER Grant ECO2016- 77900-

    The generalized index of maximum and minimum level and its application in decision making

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    The index of maximum and minimum level is a very useful technique, especially for decision making, which uses the Hamming distance and the adequacy coefficient in the same problem. In this paper, we suggest a generalization by using generalized and quasi-arithmetic means. As a result, we will get the generalized ordered weighted averaging index of maximum and minimum level (GOWAIMAM) and the Quasi-OWAIMAAM operator. These new aggregation operators generalize a wide range of particular cases such as the generalized index of maximum and minimum level (GIMAM), the OWAIMAM, the ordered weighted quadratic averaging IMAM (OWQAIMAM), and others. We also develop an application of the new approach in a decision making problem about selection of products.generalized mean, index of maximum and minimum level, quasi-arithmetic mean, decision making, owa operator

    Finding a Collective Set of Items: From Proportional Multirepresentation to Group Recommendation

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    We consider the following problem: There is a set of items (e.g., movies) and a group of agents (e.g., passengers on a plane); each agent has some intrinsic utility for each of the items. Our goal is to pick a set of KK items that maximize the total derived utility of all the agents (i.e., in our example we are to pick KK movies that we put on the plane's entertainment system). However, the actual utility that an agent derives from a given item is only a fraction of its intrinsic one, and this fraction depends on how the agent ranks the item among the chosen, available, ones. We provide a formal specification of the model and provide concrete examples and settings where it is applicable. We show that the problem is hard in general, but we show a number of tractability results for its natural special cases
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