Ambulance location under stochastic demand: A sampling approach

Publication date: Available online 1 September 2015 Source:Operations Research for Health Care Author(s): Stefan Nickel, Melanie Reuter-Oppermann, Francisco Saldanha-da-Gama In this paper, we investigate the problem of choosing the location and number of ambulances and their bases in a certain region. The goal is to minimize the total cost for installing (and maintaining) these facilities but assuring a minimum coverage level. Demand is assumed to be stochastic. A scenario-indexed formulation is considered for the problem. By using a small illustrative example we show that even when demand can be captured by a finite number of scenarios, rapidly the number of scenarios becomes too large, thus preventing the effective use of the model. We also show that the possibility of considering just one sample of scenarios can lead to a totally misleading solution. These insights motivate the development of a sampling approach in which we draw several samples of scenarios and solve the restricted model associated with each of them. The sample of optimal values obtained by this procedure can be combined in order to estimate the optimal value of the original problem. The same happens with the sample of optimal solutions obtained, which can be combined heuristically to produce a feasible solution to the whole problem. We test the new approach using a set of random instances.
Source: Operations Research for Health Care - Category: Hospital Management Source Type: research