Optimizing large-scale emergency medical system operations on highways using the hypercube queuing model
In this study, we present a series of well-known optimization methods to address two related decisions associated with the design of large-scale ambulance operations on highways: (1) The question of location, and (2) the issue of districting. As a result of computer storage and runtime constraints, previous approaches have only considered small-to-moderate scale problem scenarios, generally employing exact hypercube queuing models integrated into optimization procedures. We overcome these limitations here by embedding a fast and accurate hypercube approximation algorithm adapted for partial backup dispatch policies in single- and multi-start greedy heuristics. The proposed methods are tested on small-to-large-scale problems involving up to 100 ambulances. The results suggest that our approach is a viable alternative for the analysis and configuration of large-scale highway emergency medical systems, providing reasonable accuracy and affordable run times.
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