ARBEITSBERICHTE DES INSTITUTS FÜR UNTERNEHMENSFÜHRUNG, RUHR-UNIVERSITÄT BOCHUM, 118 (2016)
In this paper, a data-based approach is proposed providing emergency medical service decision makers to efficiently deploy their resources. By increasing data accuracy, timely adjustments can be made to emergen-cy resources. Nevertheless, in state-of-the-art literature, the location of ambulances is optimized, while staff requirements are neglected making such approaches not practicable for real-world applications. In this pa-per, ambulance allocation and shift scheduling of crews are linked in a linear integer optimization model to ensure comprehensive decision support. By using a real-world case study, we show that ambulance planning that neglects staff requirements is not practicable, since staff cannot be used as flexibly as ambulances. Considering shift patterns, there will be a slack of extra ambulances scheduled in addition to the required number. To use these ambulances in the best possible manner, different objective functions are proposed. The influence of these objective functions and the resulting positioning of emergency resources on real-world outcome measures are analyzed via a detailed discrete event simulation study. We show the ad-vantages of the suggested comprehensive approach, which results in a higher response time threshold. Ap-plying our model, it is possible to make use of the available data and determine practicable, optimal location of ambulances according to given shift patterns.