Rabe, M.; Tordecilla, R. D.; Martins, L. do C.; Chicaiza-Vaca, J.; Juan, A. A.: Supporting Hospital Logistics During the First Months of the COVID-19 Crisis: A Simheuristic for the Stochastic Team Orienteering Problem. In: Kim, S.; Feng, B.; Smith, K.; Masoud, S.; Zheng, Z.; Szabo, C.; Loper, M.: (eds,): Proceedings of the 2021 Winter Simulation Conference. Piscataway: IEEE 2021, DOI 10.1109/WSC52266.2021.9715337.

The unexpected crisis posed by the COVID-19 pandemic in 2020 caused that items such as face shields and ear savers were highly demanded. In the Barcelona area, hundreds of volunteers employed their home 3D-printers to produce these elements. After the lockdown, they had to be collected by a reduced group of volunteer drivers, who transported them to several consolidation centers. These activities required a daily agile design of efficient routes, especially considering that routes should not exceed a maximum time threshold to minimize drivers’ exposure. These constraints limit the number of houses that could be visited. Moreover, travel and service times are considered as random variables. This logistics challenge is modeled as a stochastic team orienteering problem. Our main performance indicator is the collected reward, which should be maximized. This problem is solved by employing a biased-randomized simheuristic algorithm, which is capable of generating high-quality solutions in short computing times.