We present a decision suppport tool for the comparison and selection of projects of integrated renovation of derelict buildings and areas for the purpose of urban regeneration. Each project is defined as a subset of derelict properties to renovate together with their respective designated use, and is scored by the decision support tool on two criteria: Expected effort and estimated effectiveness in terms of improved urban capabilities in the urban area of interest. The expected effort is estimated as a global transformation cost, factoring in legal and management overhead costs as well as possible economies of scale. The effectiveness in evaluated in terms of extension of urban capabilities centred on walkable distances. We have implemented a bi-objective evolutionary search algorithm to address the computational complexity of the problem of search for efficient (non-dominated) projects over the two criteria. For the purpose of illustration, we present an example case-study application on the historical core of the city of Sassari, Italy.

A DECISION SUPPORT TOOL on DERELICT BUILDINGS for URBAN REGENERATION / Blěcí, I.; Cecchini, A.; Minchilli, M.; Tedeschi, L. F.; Trunfio, G. A.. - 4:(2018), pp. 19-25. (Intervento presentato al convegno 3rd International Conference on Smart Data and Smart Cities, SDSC 2018; Delft; Netherlands; 4 October 2018 through 5 October 2018) [10.5194/isprs-annals-IV-4-W7-19-2018].

A DECISION SUPPORT TOOL on DERELICT BUILDINGS for URBAN REGENERATION

Cecchini, A.;Minchilli, M.;Tedeschi, L. F.;Trunfio, G. A.
2018-01-01

Abstract

We present a decision suppport tool for the comparison and selection of projects of integrated renovation of derelict buildings and areas for the purpose of urban regeneration. Each project is defined as a subset of derelict properties to renovate together with their respective designated use, and is scored by the decision support tool on two criteria: Expected effort and estimated effectiveness in terms of improved urban capabilities in the urban area of interest. The expected effort is estimated as a global transformation cost, factoring in legal and management overhead costs as well as possible economies of scale. The effectiveness in evaluated in terms of extension of urban capabilities centred on walkable distances. We have implemented a bi-objective evolutionary search algorithm to address the computational complexity of the problem of search for efficient (non-dominated) projects over the two criteria. For the purpose of illustration, we present an example case-study application on the historical core of the city of Sassari, Italy.
2018
A DECISION SUPPORT TOOL on DERELICT BUILDINGS for URBAN REGENERATION / Blěcí, I.; Cecchini, A.; Minchilli, M.; Tedeschi, L. F.; Trunfio, G. A.. - 4:(2018), pp. 19-25. (Intervento presentato al convegno 3rd International Conference on Smart Data and Smart Cities, SDSC 2018; Delft; Netherlands; 4 October 2018 through 5 October 2018) [10.5194/isprs-annals-IV-4-W7-19-2018].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11388/218387
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