A cardinality-constrained robust approach for the ambulance location and dispatching problem

Emergency Medical Services (EMS) systems aim to provide immediate care in case of emergency. A careful planning is a major prerequisite for the success of an EMS system, in particular to reduce the response time. Unfortunately, the demand for emergency services is highly variable and uncertainty should not be neglected while planning the activities. Several optimization models have been proposed in the literature to deal with EMS planning-related problems, e.g. the Ambulance Location and Dispatching Problem (ALDP). However, most of the models are deterministic and neglect demand uncertainty. In this paper, we formulate and validate a robust counterpart of the ALDP to deal with demand uncertainty, exploiting the cardinality-constrained approach. Numerical experiments inspired by a real case show promising results and prove the practical applicability of the approach.