Strategic Planning for Setting Up Base Stations in Emergency Medical Systems. Ghosh, S. & Varakantham, P. In
Strategic Planning for Setting Up Base Stations in Emergency Medical Systems [link]Paper  abstract   bibtex   
Emergency Medical System (EMS) is an important component of public healthcare services. The construction of base stations at the ”right” locations is critical to the performance of an EMS and is the main focus of this paper. This is a computationally challenging task because of the: (a) Exponentially large action space since the set of potential locations where bases can be constructed is typically large; (b) Uncertainty and dynamism in availability of budget. In fact, budget typically arrives over time and in different chunks; (c) Direct impact on the performance of the ambulance allocation problem, where we decide allocation of ambulances to bases. We present an incremental greedy approach to discover the placement of bases that maximises the service level of EMS. Using the properties of submodular optimisation we show that our greedy algorithm provides quality guaranteed solutions for one of the objectives employed in real EMSs. Furthermore, we validate our derived policy by employing a real-life event driven simulator that incorporates the real dynamics of EMS. Finally we show the utility of our approaches on a real-world dataset from a large asian city and demonstrate significant improvement over the best known approaches from literature.
@inproceedings {icaps16-207,
    track    = {​​​Applications Track},
    title    = {Strategic Planning for Setting Up Base Stations in Emergency Medical Systems},
    url      = {http://www.aaai.org/ocs/index.php/ICAPS/ICAPS16/paper/view/13031},
    author   = {Supriyo Ghosh and  Pradeep Varakantham},
    abstract = {Emergency Medical System (EMS) is an important component of public healthcare services. The construction of base stations at the ”right” locations is critical to the performance of an EMS and is the main focus of this paper. This is a computationally challenging task because of the: (a) Exponentially large action space since the set of potential locations where bases can be constructed is typically large; (b) Uncertainty and dynamism in availability of budget. In fact, budget typically arrives over time and in different chunks; (c) Direct impact on the performance of the ambulance allocation problem, where we decide allocation of ambulances to bases. We present an incremental greedy approach to discover the placement of bases that maximises the service level of EMS. Using the properties of submodular optimisation we show that our greedy algorithm provides quality guaranteed solutions for one of the objectives employed in real EMSs. Furthermore, we validate our derived policy by employing a real-life event driven simulator that incorporates the real dynamics of EMS. Finally we show the utility of our approaches on a real-world dataset from a large asian city and demonstrate significant improvement over the best known approaches from literature.},
    keywords = {Evaluation; testing; and validation of P&S applications,Description and modeling of novel application domains}
}
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