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Conventional discharge targets like '80% by 11 a.m.' and others that spread targets across the day to balance staff workload freed up the equivalent of nine available beds for incoming patient flow, significantly reducing time spent waiting for an inpatient bed, hospital LOS and occupancy, and delivering much needed improvements in NEAT performance. While different strategies and workload distributions may suit individual hospital services, the study makes a strong case for improving 'early in the day' discharge timeliness to deliver better ED flow.

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This article describes a prototype travel recommender system called the Electronic Travel Planner (ETP), which prepares travel itineraries for tourists. The system is driven by models of a traveler's preferences and requirements, and makes reference to databases containing information pertaining to tourism and travel products. Its main tasks are to select destinations for the traveler to visit, to decide which tours or attractions are to be taken, and to compose a detailed itinerary linking up the chosen components. These tasks entail difficult optimization problems, which the prototype addresses by means of an heuristic problem-solving framework. Computational tests confirm the effectiveness of the methods used, and suggest that an automated approach will be feasible in full-scale travel planning applications.