Transport network downsizing based on optimal sub-network

Transportation networks are sized to efficiently achieve some set of service objectives. Under particular circumstances, such as the COVID-19 pandemic, demand for transportation can significantly change, both qualitatively and quantitatively, resulting in an over-capacitated less efficient network. In this paper, we address issue by proposing a framework resizing network cope with new demand. The includes model determine optimal sub-network that guarantees following: (i) minimal access time from any node urban has not excessively increased compared original network; (ii) delay induced on itinerary removal nodes increased; (iii) number removed is within preset known factor. A solution if it induces global delay. We modelled problem Mixed Integer Linear Program applied public bus Lyon, France, case study. order respond operational issues, also decision tool helps planners decide which lines close ones leave open according specific trade-off preferences. results real data Lyon show MILP be used feed tool, leading scenarios planners.