A model to support the decision-making in urban regeneration

•Urban regeneration represents an opportunity for sustainable development and smart growth of towns.•The process involves different categories of stakeholders, each of them with different and contrasting needs.•The problem is solved through the construction of the model based on the objective functions.•The model allows to identify the use of the urban area to be regenerated that represents the best possible compromise.•The model is a tool to support investment decision-making. Urban regeneration represents an opportunity for sustainable development and smart growth of towns. The European best practices of urban regeneration demonstrate its effectiveness to valorize obsolete existing buildings, through integrated design of energy and structural upgrade. In countries of southern Europe, characterized by medium to high seismic risk, programs of urban regeneration, would make it possible to reduce buildings vulnerability, through seismic upgrade/retrofit interventions, or alternatively, through demolition and reconstruction interventions, when the previous ones do not allow the improvement of seismic performance of building structures in order to ensure adequate levels of safety. The research work sets out a real case for a possible process of urban regeneration, of a residential neighborhood located in the city of Matera, through demolition of existing buildings and then their reconstruction in the same volume size or, eventually, increased in relation to the premiums of volume required by current regulations. The process involves three different categories of stakeholders: residents, public sector and private investor responsible for executing and financing of the entire processing. Each of them with different and contrasting needs. At the end of the process, the new surfaces should be redistributed between residents and private investor. These shares, with the volumetric premium, constitute the unknown variables of the problem and, their possible combinations represent the different possible options of intervention. The problem is solved through the construction of the model based on the objective functions, expressed by utility functions, defined for each stakeholder. The search for the optimum solution, which is able to balance the different utilities, is carried out with Multi-objective linear programming.