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The Non-Emergency Patient Transport Modelled as a Team Orienteering Problem

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Operations Research and Enterprise Systems (ICORES 2015)

Abstract

This work presents an improved model to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving Orienteering Problems is presented, and this heuristic provides good results in terms of accuracy and computation time. Euclidean instances as well as asymmetric real data gathered from Google maps were used, and the model has a promising performance mainly with asymmetric cost matrices.

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Acknowledgements

This work has been partially supported by the project GATOP - Genetic Algorithms for Team Orienteering Problem (Ref PTDC/EME-GIN/120761/2010), financed by national funds by FCT/MCTES, and co-funded by the European Social Development Fund (FEDER) through the COMPETE - Programa Operacional Fatores de Competitividade (POFC) Ref FCOMP-01-0124-FEDER-020609.

This work has been partially supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.

The authors would like to thank the NEOS Server at the University of Wisconsin in Madison for providing support to this study.

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Correspondence to José A. Oliveira .

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Oliveira, J.A., Ferreira, J., Dias, L., Figueiredo, M., Pereira, G. (2015). The Non-Emergency Patient Transport Modelled as a Team Orienteering Problem. In: de Werra, D., Parlier, G., Vitoriano, B. (eds) Operations Research and Enterprise Systems. ICORES 2015. Communications in Computer and Information Science, vol 577. Springer, Cham. https://doi.org/10.1007/978-3-319-27680-9_10

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  • DOI: https://doi.org/10.1007/978-3-319-27680-9_10

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