With the aging of the population and the demand for cost-efficiency, logistics and planning in hospitals are becoming increasingly important. In many countries, hospitals are organized in a decentralized fashion, with (medical) departments and units having a high degree of autonomy in management and planning. Research institute develops computational approaches to the optimization of patient flow logistics in hospitals, i.e. concerning the various pathways of inpatients moving through various units in a hospital. Sceduling decisions in hospitals are often taken in a decentralized way. This means that different specialized hospital units make autonomous decisions relating to such issues as patient admissions and schedules of shared resources. Decision support in such a setting requires different methodes and techniques to those described in the majority to those described. Dynamic decision support for hospital resource management and the prediction of future resource occupancy. Agent-based model. Optimizing of conflicting objectives.
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