Decision support systems play an increasingly important role in disaster management research. Coordination of rescue units during disaster response is one of the many areas which may benefit from this development. Time pressure, resource shortages, different capabilities of rescue units and the interdependence of scheduling and allocation tasks belong to the key challenges which emergency operation centers have to cope with. This paper proposes a non-linear optimization model and suggests a Monte Carlo-based heuristic solution procedure. We computationally benchmark our heuristic with a procedure that is applied in practice. Results of our study show that the Monte-Carlo heuristic is superior to the state-of-the art approach in terms of aggregated harm by up to 40%. However, our simulations also reveal that the time our heuristic needs to process medium-sized instances (100 incidents, 50 rescue units) on a PC is a few hours and that more powerful real-time computing capabilities are required.
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