Capacity Allocation for Sequentially Delivered Services

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This doctoral thesis examines the problem where different c1asses of customers can book different types of service in advance and the service company has to respond immediately to the booking request by either rejecting it or setting the day and time of the service. The objective is to maximize the average profit. The problem is modeled as a Markov decision process and solved using dynamic programming, simulationbased approximate dynamic programming, and simple heuristics. In an experimental study the different algorithms are evaluated employing data from two providers that operate magnetic resonance imaging scanners.