A mixed-integer programming model for identifying intuitive ambulance dispatching policies

Markov decision process models and algorithms can be used to identify optimal policies for dispatching ambulances spatially distributed customers, where the indicate ambulance dispatch each customer type in state. Since solutions are dependent on state variables, they may not always correspond a simple set of rules when implementing practice. Restricted that conform priority list desirable use practice, since such transparent, explainable, easy implement. A policy is an ordered indicates preferred order subject availability. This paper proposes constrained model identifying formulated as mixed integer programming model, does extend space, solved using standard algorithms. series computational examples illustrate benefit intuitive policies. The have objective function values close those unrestricted superior heuristics.