Multi-Criteria Decision Analysis (MCDA) and in particular the Analytic Hierarchy Process (AHP) is widely used in construction thanks to its versatility and ability to involve qualitative and quantitative data in the analysis. On the other hand, many complex problems are difficult to be solved because of the large amount of information to be considered. In this paper, an Augmented Reality based Decision Making (AR-DM) is proposed to get a novel MCDA following the hierarchical structure of the AHP. For the first time, the AR immersive environment is combined with the Simos-Roy-Figueira method to provide a large amount of visual information during the decision phase. The proposed approach is tested to support the selection of an experimental Precast Concrete Panel for RC buildings retrofitting. Finally, a comparison with the classical approach and two other improved version of the AHP procedure is performed to validate and show the potential of the method.

Augmented reality based- decision making (AR-DM) to support multi-criteria analysis in constructions

Valentino Sangiorgio
Primo
;
2021-01-01

Abstract

Multi-Criteria Decision Analysis (MCDA) and in particular the Analytic Hierarchy Process (AHP) is widely used in construction thanks to its versatility and ability to involve qualitative and quantitative data in the analysis. On the other hand, many complex problems are difficult to be solved because of the large amount of information to be considered. In this paper, an Augmented Reality based Decision Making (AR-DM) is proposed to get a novel MCDA following the hierarchical structure of the AHP. For the first time, the AR immersive environment is combined with the Simos-Roy-Figueira method to provide a large amount of visual information during the decision phase. The proposed approach is tested to support the selection of an experimental Precast Concrete Panel for RC buildings retrofitting. Finally, a comparison with the classical approach and two other improved version of the AHP procedure is performed to validate and show the potential of the method.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/765443
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