Model predictive control to mitigate the COVID-19 outbreak in a multi-region scenario

The COVID-19 outbreak is deeply influencing the global social and economic framework, due to restrictive measures adopted worldwide by governments to counteract the pandemic contagion. In multi-region areas such as Italy, where the contagion peak has been reached, it is crucial to find targeted and coordinated optimal exit and restarting strategies on a regional basis to effectively cope with possible onset of further epidemic waves, while efficiently returning the economic activities to their standard level of intensity. Differently from the related literature, where modeling and controlling the pandemic contagion is typically addressed on a national basis, this paper proposes an optimal control approach that supports governments in defining the most effective strategies to be adopted during post-lockdown mitigation phases in a multi-region scenario. Based on the joint use of a non-linear Model Predictive Control scheme and a modified Susceptible-Infected-Recovered (SIR)-based epidemiological model, the approach is aimed at minimizing the cost of the so-called non-pharmaceutical interventions (that is, mitigation strategies), while ensuring that the capacity of the network of regional healthcare systems is not violated. In addition, the proposed approach supports policy makers in taking targeted intervention decisions on different regions by an integrated and structured model, thus both respecting the specific regional health systems characteristics and improving the system-wide performance by avoiding uncoordinated actions of the regions. The methodology is tested on the COVID-19 outbreak data related to the network of Italian regions, showing its effectiveness in properly supporting the definition of effective regional strategies for managing the COVID-19 diffusion.

Multi-criteria decision-making for sustainable metropolitan cities assessment

The recent development of metropolitan cities, especially in Europe, requires an effective integrated management of city services, infrastructure, and communication networks at a metropolitan level. A preliminary step towards a proper organizational and management strategy of the metropolitan city is the analysis, benchmarking and optimization of the metropolitan areas through a set of indicators coherent with the overall sustainability objective of the metropolitan city. This paper proposes the use of the Analytic Hierarchy Process multi-criteria decision making technique for application in the smart metropolitan city context, with the aim of analysing the sustainable development of energy, water and environmental systems, through a set of objective performance indicators. Specifically, the 35 indicators defined for the Sustainable Development of Energy, Water and Environment Systems Index framework are used. The application of the approach to the real case study of four metropolitan areas (Bari, Bitonto, Mola, and Molfetta) in the city of Bari (Italy) shows its usefulness for the local government in benchmarking metropolitan areas and providing decision indications on how to formulate the sustainable development strategy of the metropolitan city. Based on the Analytic Hierarchy Process characteristics, the results highlight that although one specific area (Mola in the considered case) is globally ranked at the first place, it is only ranked first with respect to some dimensions. Such a result has strong implications for the metropolitan city's manager who has the possibility to identify and implement targeted actions, which may be designed ad hoc to improve specific dimensions based on the current state of the city, thus maximizing the efficiency and effectiveness of the actions undertaken for the sustainable development of energy, water and environmental systems of the whole metropolitan city.