Multiple Criteria Decision Aiding (MCDA) gives not only a toolbox, but, overall, a well developed methodology to support decision-making processes. MCDA is particularly useful in the context of sustainability assessment and urban and territorial planning, where a complex and inter-connected range of environmental, social and economic issues must be taken into consideration. Moreover, the analysis of the possible interactions among the considered criteria is of particular importance for assessing the sustainability of a certain transformation. The paper proposes an application of the Non Additive Robust Ordinal Regression approach for the selection of a new landfill location among several alternatives.

Non Additive Robust Ordinal Regression for Urban and Territorial Planning: an application for siting an urban waste landfill / Angilella, S.; Bottero, MARTA CARLA; Corrente, S.; Ferretti, Valentina; Greco, Salvatore; Lami, ISABELLA MARIA. - STAMPA. - (2013), pp. 309-309. (Intervento presentato al convegno 22 International Conference on Multiple Criteria Decision Making tenutosi a Malaga (Spain) nel 17-21 June 2013).

Non Additive Robust Ordinal Regression for Urban and Territorial Planning: an application for siting an urban waste landfill

BOTTERO, MARTA CARLA;FERRETTI, VALENTINA;GRECO, Salvatore;LAMI, ISABELLA MARIA
2013

Abstract

Multiple Criteria Decision Aiding (MCDA) gives not only a toolbox, but, overall, a well developed methodology to support decision-making processes. MCDA is particularly useful in the context of sustainability assessment and urban and territorial planning, where a complex and inter-connected range of environmental, social and economic issues must be taken into consideration. Moreover, the analysis of the possible interactions among the considered criteria is of particular importance for assessing the sustainability of a certain transformation. The paper proposes an application of the Non Additive Robust Ordinal Regression approach for the selection of a new landfill location among several alternatives.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2510881
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