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Home Health Care (HHC) human resource management is a complex process. Moreover, as patients are assisted for a long time, their demand for care evolves in terms of type and frequency of visits. Under continuity of care, this uncertain evolution must be considered even when scheduling the visits in the short-term, as the corresponding operator-to-patient assignments could generate overtimes and unbalanced workloads in the long-term, which must be fixed by reassigning some patients and deteriorating the continuity of care. On the other hand, the operator-to-patient assignment problem under continuity of care over a long time period could generate solutions that are infeasible when the scheduling constraints are considered. We analyze the trade-offs between the two problems, to analyze the conditions in which they can be sequentially solved or an integration is required. In particular, we take an assignment and scheduling model for short-term planning, an operator-to-patient assignment model over a long time horizon, and we merge them into a new combined model. Results on a set of realistic instances show that the combined model is necessary when the number of patterns is limited and the variability of patients' demands is high, whereas simpler models deserve to be applied in less critical situations.

In urban transportation, combined mode trips are increasing in importance due to current urban transportation polices which encourage the use of transit through the creation of apposite parking lots and improvements in the public transportation system. It is widely recognized that parking policy plays an important role in urban management: parking policy measures not only affect the parking system, but also generate impacts to the transport and socioeconomic system of a city. The present paper attempts to expand on previous research concerning the development of models to capture drivers' parking behavior. It introduces in the modeling structure additional variables to the ones usually employed, with which the drivers' behavior to changes in prices and distances (mainly walking) are better captured. We develop a network model that represents trips as a combination of private and transit modes. A graph representing four different modes (car, bus, metro and pedestrian) is defined and a set of free park and ride facilities is introduced to discourage the use of private cars. An algorithm that evaluates the location and the effects of the parking price variation using multi-modal shortest paths is proposed together with an application to the City of Rome. Computational results are shown.