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Titel
Multicriteria analysis under uncertainty with IANUS : method and empirical results / Bernd Klauer; Martin Drechsler; Frank Messner. Departments of Economics, Sociology and Law (OEKUS) and Ecological Modelling
VerfasserKlauer, Bernd ; Drechsler, Martin ; Messner, Frank
ErschienenLeipzig ; Halle : UFZ-Umweltforschungszentrum Leipzig-Halle GmbH, 2002
UmfangOnline-Ressource (PDF-Datei: 27 S., 0,13 MB) : graph. Darst.
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Parallel als Druckausg. erschienen
SpracheEnglisch
SerieUFZ-Diskussionspapiere ; 2/2002
URNurn:nbn:de:gbv:3:2-77426 
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Multicriteria analysis under uncertainty with IANUS [0.13 mb]
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IANUS is a method for aiding public decision-making that supports efforts towards sustainable development and has a wide range of application. IANUS stands for Integrated Assessment of Decisions uNder Uncertainty for Sustainable Development. This paper introduces the main features of IANUS and illustrates the method using the results of a case study in the Torgau region (eastern Germany). IANUS structures the decision process into four steps: scenario derivation criteria selection modeling evaluation. Its overall aim is to extract the information needed for a sound responsible decision in a clear transparent manner. The method is designed for use in conflict situations where environmental and socioeconomic effects need to be considered and so an interdisciplinary approach is required. Special emphasis is placed on a broad perception and consideration of uncertainty. Three types of uncertainty are explicitly taken into account by IANUS: development uncertainty (uncertainty about the social economic and other developments that affect the consequences of decision) model uncertainty (uncertainty associated with the prediction of the effects of decisions) and weight uncertainty (uncertainty about the appropriate weighting of the criteria). The backbone of IANUS is a multicriteria method with the ability to process uncertain information. In the case study the multicriteria method PROMETHEE is used. Since PROMETHEE in its basic versions is not able to process uncertain information an extension of this method is developed here and described in detail.