Displaying similar documents to “Preface to the Special Issue”

A model of decision with linguistic knowledge.

María Teresa Lamata Jiménez (1994)

Mathware and Soft Computing

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The aim of this paper is to develop a new aggregating method for the decision problem in which the possible values of rewards are known in linguistic terms. We show new operators for solving this problem, as well as the way in which OWA operators provide us with an adequate framework for representing the optimism degree of the decision maker in case we have no information about the real state.

A classical decision theoretic perspective on worst-case analysis

Moshe Sniedovich (2011)

Applications of Mathematics

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We examine worst-case analysis from the standpoint of classical Decision Theory. We elucidate how this analysis is expressed in the framework of Wald's famous Maximin paradigm for decision-making under strict uncertainty. We illustrate the subtlety required in modeling this paradigm by showing that information-gap's robustness model is in fact a Maximin model in disguise.

Extended VIKOR as a new method for solving Multiple Objective Large-Scale Nonlinear Programming problems

Majeed Heydari, Mohammad Kazem Sayadi, Kamran Shahanaghi (2010)

RAIRO - Operations Research

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The VIKOR method was introduced as a Multi-Attribute Decision Making (MADM) method to solve discrete decision-making problems with incommensurable and conflicting criteria. This method focuses on ranking and selecting from a set of alternatives based on the particular measure of “closeness” to the “ideal” solution. The multi-criteria measure for compromise ranking is developed from the – metric used as an aggregating function in a compromise programming method. In this paper, the...

A characterization of value efficiency.

Alfonso Mateos, Sixto Ríos-Insua (1996)

Extracta Mathematicae

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An important issue in multi-attribute decision making consists of identifying the set of efficient solutions. The importance of this set is that the decision maker (DM) can restrict his attention to it, discarding all other solutions, because a nonefficient solution can never be optimal. Several methods have been developed to aid a DM in generating all or representative subsets of efficient solutions, [1] and [4], or to approximate it [7]. However most of these methods may be hard to...

Interactive compromise hypersphere method and its applications

Sebastian Sitarz (2012)

RAIRO - Operations Research

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The paper focuses on multi-criteria problems. It presents the interactive compromise hypersphere method with sensitivity analysis as a decision tool in multi-objective programming problems. The method is based on finding a hypersphere (in the criteria space) which is closest to the set of chosen nondominated solutions. The proposed modifications of the compromise hypersphere method are based on using various metrics and analyzing their influence on the original method. Applications of...

Interactive compromise hypersphere method and its applications

Sebastian Sitarz (2012)

RAIRO - Operations Research - Recherche Opérationnelle

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The paper focuses on multi-criteria problems. It presents the interactive compromise hypersphere method with sensitivity analysis as a decision tool in multi-objective programming problems. The method is based on finding a hypersphere (in the criteria space) which is closest to the set of chosen nondominated solutions. The proposed modifications of the compromise hypersphere method are based on using various metrics and analyzing their influence on the original method. Applications of...

An incremental approach to obtaining attribute reduction for dynamic decision systems

Liu Wenjun (2016)

Open Mathematics

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In the 1960s Professor Hu Guoding proposed a method of measuring information based on the idea that connotation and denotation of a concept satisfies inverse ratio rule. According to this information measure, firstly we put forward the information quantity for information systems and decision systems; then, we discuss the updating mechanism of information quantity for decision systems; finally, we give an attribute reduction algorithm for decision tables with dynamically varying attribute...