Abstract
The goal of this paper is defining a methodology for assessing priorities among interventions in the historic center of Florence, going from the conservation to the regeneration of its heritage. The possibility to re-use a building with new characterizations depends on binding and administrative issues while the optimization of resources depends on the planning and organization of the construction sites. The proposed methodology falls within the so called “mixed methods”, as it integrates within a multi-criteria model, specific degradation analysis methods and parameters for construction cost optimization. This research proposes a model that interfaces and integrates projects already running in the area already included in the. This, data will be included in the Geographic Information System with the aim of carrying out comprehensive analysis, monitoring, and management of the building heritage in the historic center of Florence that is under development. The methodology can be considered as a contribution to the Management Plan of the site of the Historic Center of Florence. In addition, the defined method, besides being is in accordance with some action projects of the second macro-area of the management plan is also in keeping with the provisions of the Municipal Operational Plan, which in Sect. 4.3 calls for a reinterpretation of the existing building stock. With the aim to preserve them, we will start from individual building monitoring, moving on to study the condition promoting the creation of joint construction sites, thus optimizing costs. Hence the methodology selects areas suitable for regeneration, whose different transformation alternatives are evaluated (HIA) and hierarchized (MCDA).
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Acampa, G., Battisti, F., Grasso, M. (2023). Decision Support System for the Management of Interventions on Buildings in the Historic Centre of Florence: From Conservation to Regeneration. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2023 Workshops. ICCSA 2023. Lecture Notes in Computer Science, vol 14111. Springer, Cham. https://doi.org/10.1007/978-3-031-37126-4_22
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