The donation-transplant network's complexity lies in the need to reconcile standardized processes and high levels of urgency and uncertainty due to organs' perishability and location. Both punctuality and reliability of air transportation service are crucial to ensure the safe outcome of the transplant. To this scope, an Integer Linear Programming (ILP) model is here proposed to determine the optimal distribution of aircraft in a given set of hubs and under the demand extracted from the Italian transplant database. This is an application of uncapacitated facility location problems, where aircraft are facilities to be located and organ transportation requests represent the demand. Two scenarios (two hubs versus three hubs) are tested under the performance point of view and over different time periods to assess the influence of variations in demand pattern and time period length on the solution.
Cacchiani, V., Malandri, C., Mantecchini, L., Paganelli, F. (2018). A study on the optimal aircraft location for human organ transportation activities. Elsevier B.V. [10.1016/j.trpro.2018.09.034].
A study on the optimal aircraft location for human organ transportation activities
Cacchiani, V.;MALANDRI, CATERINA;Mantecchini, L.;Paganelli, F.
2018
Abstract
The donation-transplant network's complexity lies in the need to reconcile standardized processes and high levels of urgency and uncertainty due to organs' perishability and location. Both punctuality and reliability of air transportation service are crucial to ensure the safe outcome of the transplant. To this scope, an Integer Linear Programming (ILP) model is here proposed to determine the optimal distribution of aircraft in a given set of hubs and under the demand extracted from the Italian transplant database. This is an application of uncapacitated facility location problems, where aircraft are facilities to be located and organ transportation requests represent the demand. Two scenarios (two hubs versus three hubs) are tested under the performance point of view and over different time periods to assess the influence of variations in demand pattern and time period length on the solution.File | Dimensione | Formato | |
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