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We began analyzing https://link.springer.com/article/10.1007/s10479-010-0787-x, but it redirected us to https://link.springer.com/article/10.1007/s10479-010-0787-x. The analysis below is for the second page.

Title[redir]:
Alternate risk measures for emergency medical service system design | Annals of Operations Research
Description:
The stochastic nature of emergency service requests and the unavailability of emergency vehicles when requested to serve demands are critical issues in constructing valid models representing real life emergency medical service (EMS) systems. We consider an EMS system design problem with stochastic demand and locate the emergency response facilities and vehicles in order to ensure target levels of coverage, which are quantified using risk measures on random unmet demand. The target service levels for each demand site and also for the entire service area are specified. In order to increase the possibility of representing a wider range of risk preferences we develop two types of stochastic optimization models involving alternate risk measures. The first type of the model includes integrated chance constraints (ICCs ), whereas the second type incorporates ICCs and a stochastic dominance constraint. We develop solution methods for the proposed single-stage stochastic optimization problems and present extensive numerical results demonstrating their computational effectiveness.

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Keywords {🔍}

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Topics {✒️}

integrated chance constraints stochastic dominance constraints month download article/chapter alternate risk measures random unmet demand maximum availability/reliability models emergency medical services stochastic dominance constraint emergency service requests facility location problems ambulance location model spatial allocation equity measurement providing equal access optimal ambulance location facility location analysis stochastic location analysis strategic facility location siting emergency services emergency response facilities selecting ambulance station privacy choices/manage cookies risk measures target service levels entire service area operations research models emergency services vehicles stochastic dominance stochastic demand ilog cplex division full article pdf reliability model applied probabilistic constraints operations research aims modelling language integer programming approach stochastic nature ambulance location probabilistic model applied ensure target levels related subjects facility location ca/aingolfsson/publications ordering uncertain prospects van der vlerk stochastic programming stochastic models check access instant access random delays

Questions {❓}

Spatial allocation of emergency medical services: minimizing the death rate or providing equal access?

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