摘要：Abstract Home health care (HHC) services are of vital importance for today's society. They allow old and frail people a self-determined living in their familiar environment. Due to the current demographic and social developments further increases in demand for HHC must be expected. Additionally, people with limited mobility or relying on medical supply usually need consistent care. Thus, HHC service providers will be faced with two challenges: an increased organizational effort due to the rising demand and the need for an anticipatory risk management. Previous research combining optimization and risk management in the field of HHC limits itself to rural regions, where nurses are solely using cars. The presented work specifically aims to deal with the peculiarities of urban regions. Together with the Austrian Red Cross (ARC), a vulnerability analysis has been conducted in order to identify the critical success factors and processes of HHC as well as potential threats. To support the daily scheduling, a Tabu Search (TS) based metaheuristic has been implemented. As nurses can choose between different transport modes (public transport, car, bike, and walking), time-dependent multimodal transport has been considered. The TS has been tested with real-world data from the ARC in Vienna to support both, daily business and scheduling in times of disasters. Significant reductions of travel and waiting times can be obtained, such that more time remains for serving the clients. Through sensitivity analysis the effects of disasters (esp. blackout, pandemics, and heat waves) are visualized and the operational limits during such events are shown.
关键词：KeywordsHome health caredecision support systemsrisk managementdisaster vulnerabilityrouting algorithmstime-dependent travel times
