A Constraint Programming Approach for Solving Patient Transportation Problems
The Patient Transportation Problem (PTP) aims to bring patients to health centers and to take them back home once the care has been delivered. All the requests are known beforehand and a schedule is built the day before its use. It is a variant of the well-known Dial-a-Ride Problem (DARP) but it has nevertheless some characteristics that complicate the decision process. Three levels of decisions are considered: selecting which requests to service, assigning vehicles to requests and routing properly the vehicles. In this paper, we propose a Constraint Programming approach to solve the Patient Transportation Problem. The model is designed to be flexible enough to accommodate new constraints and objective functions. Furthermore, we introduce a generic search strategy to maximize efficiently the number of selected requests. Our results show that the model can solve real life instances and outperforms greedy strategies typically performed by human schedulers.
This research is financed by the Walloon Region (Belgium) as part of PRESupply Project. The problem has been proposed by the CSD, a Belgian non-profit organization operating at Liège.
- 19.Beldiceanu, N., Carlsson, M., Rampon, J.X.: Global constraint catalog, (revision a) (2012)Google Scholar
- 26.Laborie, P., Rogerie, J.: Reasoning with conditional time-intervals. In: FLAIRS Conference, pp. 555–560 (2008)Google Scholar
- 27.Laborie, P., Rogerie, J., Shaw, P., Vilím, P.: Reasoning with conditional time-intervals. Part II: an algebraical model for resources. In: FLAIRS Conference, pp. 201–206 (2009)Google Scholar
- 28.Laborie, P., Rogerie, J., Shaw, P., Vilím, P.: IBM ILOG CP optimizer for scheduling. Constraints, 1–41 (2018)Google Scholar
- 30.Ngatchou, P., Zarei, A., El-Sharkawi, A.: Pareto multi objective optimization. In: 2005 Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems, pp. 84–91. IEEE (2005)Google Scholar
- 35.OscaR Team: OscaR: Scala in OR (2012). https://bitbucket.org/oscarlib/oscar
- 36.Thomas, C., Cappart, Q., Schaus, P., Rousseau, L.M.: CSPLib problem 082: Patient transportation problem. http://www.csplib.org/Problems/prob082
- 37.Godard, D., Laborie, P., Nuijten, W.: Randomized large neighborhood search for cumulative scheduling. ICAPS 5, 81–89 (2005)Google Scholar