The problem of the transportation of patients from or to some health care center given a number of vehicles of different kinds can be considered as a common Vehicle Routing Problem (VPR). However, in our particular case, the logistics behind the generation of the vehicle itineraries are affected by a high number of requirements and constraints such as the enterprise benefits, the satisfaction of the patients, and the respect of certain law regulations regarding the patients and the employees. In this work, we discuss the main aspects of the implementation of a Multi Objective Evolutionary Algorithm focused on providing a set of valid solutions to the end users of Patient Transport Services. We provide a detailed description of the process of integrating all the information on different genetic operators and multiple fitness functions. Finally, we present the preliminary results on a real-life problem from an small company that provides transport service and we compare the results that our implementation gets with the itineraries proposed by human experts.
Catania, C., Zanni-Merk, C., De Bertrand De Beuvron, F., & Collet, P. (2015). A multi objective evolutionary algorithm for solving a real health care fleet optimization problem. In Procedia Computer Science (Vol. 60, pp. 256–265). Elsevier B.V. https://doi.org/10.1016/j.procs.2015.08.125